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......@@ -13,20 +13,16 @@
\begin{document}
\title{The INFN-Tier1: the computing farm}
\author{Andrea Chierici}
\ead{andrea.chierici@cnaf.infn.it}
\author{Stefano Dal Pra}
\ead{stefano.dalpra@cnaf.infn.it}
\author{Diego Michelotto}
\ead{diego.michelotto@cnaf.infn.it}
\author{Andrea Chierici$^1$, Stefano Dal Pra$^1$, Diego Michelotto$^1$}
\address{$^1$ INFN-CNAF, Bologna, IT}
\ead{andrea.chierici@cnaf.infn.it, stefano.dalpra@cnaf.infn.it, diego.michelotto@cnaf.infn.it}
%\begin{abstract}
%\end{abstract}
\section{Introduction}
The farming group is responsible for the management of the computing resources of the centre. This implies the deployment of installation and configuration services, monitoring facilities and to fairly distribute the resources to the experiments that have agreed to run at CNAF.
The farming group is responsible for the management of the computing resources of the centre.
This implies the deployment of installation and configuration services, monitoring facilities and the fair distribution of the resources to the experiments that have agreed to run at CNAF.
%\begin{figure}
%\centering
......@@ -37,14 +33,16 @@ The farming group is responsible for the management of the computing resources o
\section{Farming status update}
During 2018 the group got reorganized: Antonio Falabella left the group and Diego Michelotto took over him. This turnover was quite harmless since Diego already was aware of many of the procedures adopted in farming group as well as of the collaborative tools used internally.
During 2018 the group got reorganized: Antonio Falabella left the group and Diego Michelotto took over him. This turnover was quite harmless since Diego was already aware of many of the procedures adopted in farming group as well as of the collaborative tools used internally.
\subsection{Computing}
It's well known that in November 2017 we suffered a flooding in our data center and so the largest part of 2018 was dedicated to restoring the facility, trying to understand how much of the computing power was damaged and how much was recoverable. We had quite a luck on blade servers (2015 tender) while on 2016 tender, most of the nodes that we thought were reusable, after some time got broken and were unrecoverable. We were able to recover working parts from the broken servers (like ram, CPUs and disks) and with those we assembled some nodes to be used as service nodes: the parts were accurately tested by a system integrator that guaranteed for us the stability and reliability of the resulting platform.
As a result of the flooding, approximately 24K HS06 got damaged.
It's well known that in November 2017 we suffered a flooding in our data center and so the largest part of 2018 was dedicated to restoring the facility,
trying to understand how much of the computing power was damaged and how much was recoverable.
We had quite a luck on blade servers (2015 tender), while on 2016 tender most of the nodes that we thought were reusable, after some time got broken and were unrecoverable. We were able to recover working parts from the broken servers (like ram, CPUs and disks) and with those we assembled some nodes to be used as service nodes: the parts were accurately tested by a system integrator that guaranteed for us the stability and reliability of the resulting platform.
As a result of the flooding, approximately 24 kHS06 got damaged.
In spring we finally installed the new tender, composed of AMD EPYC nodes, sporting more than 42K HS06, with 256GB of ram, 2x1TB SSDs and 10Gbit Ethernet network. This is the first time we adopt 10Gbit connection for WNs and we think from now on it will be a basic requirement: modern CPUs provide several cores, enabling us to pack more jobs in a single node, where a 1Gbit network speed may be a significant bottleneck. The same applies to HDDs vs SSDs: we think that modern computing nodes can provide 100\% of their capabilities only with SSDs disks.
General job execution trend can be seen in figure~\ref{farm-jobs}.
In spring we finally installed the new tender, composed of AMD EPYC nodes, providing more than 42 kHS06, with 256GB of ram, 2x1TB SSDs and 10Gbit Ethernet network. This is the first time we adopt 10Gbit connection for WNs and we think from now on it will be a basic requirement: modern CPUs provide several cores, enabling us to pack more jobs in a single node, where a 1Gbit network speed may be a significant bottleneck. The same applies to HDDs vs SSDs: we think that modern computing nodes can provide 100\% of their capabilities only with SSDs disks.
General job execution trend can be seen in Figure~\ref{farm-jobs}.
\begin{figure}
\centering
......@@ -54,47 +52,76 @@ General job execution trend can be seen in figure~\ref{farm-jobs}.
\end{figure}
\subsubsection{CINECA extension}
Thanks to an agreement between INFN and CINECA\cite{ref:cineca}, we were able to integrate a portion of Marconi cluster into our computing farm (approx. computing power of 180K HS06), reaching the total computing power of 400.000 HS06, almost doubling the power we provided last year. Thanks to the proximity of CINECA we set up a highly reliable fiber connection between the computing centers, with a very low latency, and could avoid to cache storage: all the remote nodes access storage hosted at CNAF in the exact same manner as the local nodes do. This simplifies a lot the setup and increases global farm reliability (see figure~\ref{cineca} for details on setup).
Thanks to an agreement between INFN and CINECA\cite{ref:cineca}, we were able to integrate a portion (3 racks for a total of 216 servers sporting $\sim$180 kHS06) of the Marconi cluster into our computing farm, reaching the total computing power of 400 kHS06, almost doubling the power we provided last year. Each server is equipped with a 10 Gbit uplink connection to the rack switch while each of them, in turn, is connected to the aggregation router with 4x40 Gbit links.
Due to the proximity of CINECA, we set up a highly reliable fiber connection between the computing centers, with a very low latency
(the RTT\footnote{Round-trip time (RTT) is the duration it takes for a network request to go from a starting point to a destination and back again
to the starting point.} is 0.48 ms vs. 0.28 ms measured on the CNAF LAN), and could avoid to set up a cache storage on the CINECA side:
all the remote nodes access storage resources hosted at CNAF in the exact same manner as the local nodes do.
This simplifies a lot the setup and increases global farm reliability (see Figure~\ref{cineca} for details on setup).
\begin{figure}
\centering
\includegraphics[keepaspectratio,width=12cm]{cineca.png}
\caption{INFN-T1 farm extension to CINECA}
\label{cineca}
\centering
\includegraphics[keepaspectratio,width=12cm]{cineca.png}
\caption{INFN-T1 farm extension to CINECA}
\label{cineca}
\end{figure}
Nodes at CINECA are setup with standard HDDs and since so many cores are available per node, we hit a bottleneck, having to slightly reduce the amount of jobs per node, that generally equals the number of cores. It's important to notice that we did not reach this limit with the latest tender we purchased, since it comes with 2 enterprise class SSDs.
During 2018 we kept using also the Bari ReCaS farm extension, with a reduced set of nodes that provided approx. 10k HS06. See 2017 AR for details on the setup.
These nodes have undergone several reconfigurations due to both the hardware and the type of workflow of the experiments.
In April we had to upgrade the BIOS to overcome a bug which was preventing the full resource usage,
limiting what we were getting from the nodes to $\sim$78\% of the total.
Moreover, since nodes at CINECA are setup with standard HDDs and since so many cores are available per node, we hit a bottleneck.
To mitigate this limitation, a reconfiguration of the local RAID configuration of disks has been
done\footnote{The initial choice of using RAID-1 for local disks instead of RAID-0 proved to slow down the system even if safer from an operational point of view.} and the amount of jobs per node was slightly reduced (generally this equals the number of logical cores). It's important to notice that we did not reach this limit with the latest tender we purchased, since it comes with two enterprise class SSDs.
During 2018 we kept using also the Bari ReCaS farm extension,
with a reduced set of nodes that provided approximately 10 kHS06\cite{ref:ar17farming}.
\subsection{Hardware resources}
Hardware resources for farming group are quite new and a refresh was not foreseen during this year. The main concern is on the two different virtualization infrastructures, that only required a warranty renewal. Since we were able to recover a few parts from the flood-damaged nodes, we were able to acquire a 2U 4 node enclosure to be used as the main resource provider for the forthcoming HTCondor instance.
Hardware resources for farming group are quite new, and a refresh was not foreseen during 2018. The main concern is on the two different virtualization infrastructures, that only required a warranty renewal. Since we were able to recover a few parts from the flood-damaged nodes, we were able to acquire a 2U 4 node enclosure to be used as the main resource provider for the forthcoming HTCondor instance.
\subsection{Software updates}
During 2018 we completed the migration from SL6 to CentOS7, on all the farming nodes. The configurations have been stored on our provisioning system: with the WNs the migration process has been rather simple, while with CEs and UIs we took extra care and proceed one at a time in order to guarantee continuity to the service. The same configurations have been used to upgrade LHCb-T2 and INFN-BO-T3, with minimal modifications. All the modules produced for our site can easily be exported to other sites, willing to perform the same update.
As already said the update involved all the services with just a small number of exceptions: CMS experiment is using PhEDEx\cite{ref:phedex}, a system that provides the data placement and the file transfer system that is incompatible with CentOS7. Since the system will be phased out in mid 2019, we agreed with the experiment to not perform any update. Same thing happened with a few legacy UIs and some services for the CDF experiment, that are involved in a LTDP project (more details in next year report).
During 2018 we completed the migration from SL6 to CentOS7 on all the farming nodes. The configurations have been stored on our provisioning system:
with the WNs the migration process has been rather simple, while with CEs and UIs we took extra care and proceeded one at a time in order to guarantee continuity
to the service. The same configurations have been used to upgrade LHCb-T2 and INFN-BO-T3, with minimal modifications.
All the modules produced for our site can easily be exported to other sites willing to perform the same update.
As already said, the update involved all the services with just a small number of exceptions: CMS experiment is using PhEDEx\cite{ref:phedex}, a system that provides the data placement and the file transfer system that is incompatible with CentOS7. Since the system will be phased out in mid 2019, we agreed with the experiment to not perform any update. Same thing happened with a few legacy UIs and some services for the CDF experiment, that are involved in a LTDP project (more details in next year report).
In any case, if an experiment needs a legacy OS, like SL6, on all the Worker Nodes we provide a container solution based on singularity\cite{ref:singu} software.
Singularity enables users to have full control of their environment through containers: it can be used to package entire scientific workflows, software and libraries, and even data. This avoids the T1 users to ask farming sysadmin to install any software, since everything can be put container and run. Users are in control of the extent to which containers interacts with its host: there can be seamless integration, or little to no communication at all.
Singularity enables users to have full control of their environment through containers: it can be used to package entire scientific workflows, software and libraries, and even data. This avoids the T1 users to ask farming sysadmin to install any software, since everything can be put in a container and run. Users are in control of the extent to which containers interacts with its host: there can be seamless integration, or little to no communication at all.
Year 2018 has been terrible from a security point of view. Several critical vulnerabilities have been discovered, affecting data-center CPUs and major software stacks: the major ones were meltdown and spectre~\cite{ref:meltdown} (see figure~\ref{meltdown} and~\ref{meltdown2}). These discoveries required us to promptly intervene in order to mitigate and/or correct these vulnerabilities, applying software updates (this mostly breaks down to updating Linux kernel and firmware) that most of the times required to reboot the whole farm. This impacts greatly in term of resource availability, but it's mandatory in order to prevent security issues and possible sensitive data disclosures. Thanks to our internally-developed dynamic update procedure, patch application is smooth and almost automatic, avoiding farm staff to waste a lot of time.
Year 2018 has been terrible from a security point of view.
Several critical vulnerabilities have been discovered, affecting data-center CPUs and major software stacks:
the major ones were Meltdown and Spectre~\cite{ref:meltdown} (see Figure~\ref{meltdown} and~\ref{meltdown2}).
These discoveries required us to promptly intervene in order to mitigate and/or correct these vulnerabilities,
applying software updates (this mostly breaks down to updating Linux kernel and firmware) that most of the times required to reboot the whole farm.
This impacts greatly in term of resource availability, but it's mandatory in order to prevent security issues and possible sensitive data disclosures.
Thanks to our internally-developed dynamic update procedure, patch application is smooth and almost automatic, avoiding waste of time for the farm staff.
\begin{figure}
\centering
\includegraphics[keepaspectratio,width=12cm]{meltdown.jpg}
\includegraphics[width=0.5\textwidth]{meltdown.jpg}
%\includegraphics[keepaspectratio,width=12cm]{meltdown.jpg}
\caption{Meltdown and Spectre comparison}
\label{meltdown}
\end{figure}
\begin{figure}
\centering
\includegraphics[keepaspectratio,width=12cm]{meltdown2.jpg}
%\includegraphics[keepaspectratio,width=12cm]{meltdown2.jpg}
\includegraphics[width=0.5\textwidth]{meltdown2.jpg}
\caption{Meltdown attack description}
\label{meltdown2}
\end{figure}
\subsection{HTCondor udpate}
INFN-T1 decided to migrate to HTCondor from LSF for several reasons. The main one is that this software has proved to be extremely scalable and ready to stand the forthcoming challenges that High Luminosity LHC will raise in our research community in the near future. Moreover many of the other T1s involved in LHC have announced the transition to HTCondor or have already completed it, not to consider the fact that our current batch system, LSF, is no longer under warranty, since INFN decided not to renew the contract with IBM (the provider of this software now re-branded ``Spectrum LSF''), in order to save money and considering the alternative given by HTCondor.
\subsection{HTCondor update}
INFN-T1 decided to migrate to HTCondor from LSF for several reasons.
The main one is that this software has proved to be extremely scalable and ready to stand the forthcoming challenges that High Luminosity LHC will raise
in our research community in the near future. Moreover, many of the other T1s involved in LHC have announced the transition to HTCondor or have already completed it,
not to consider the fact that our current batch system, LSF, is no longer under warranty, since INFN decided not to renew the contract with IBM
(the provider of this software now re-branded ``Spectrum LSF''), in order to save money and consider the alternative given by HTCondor.
\section{DataBase service: Highly available PostgreSQL}
In 2013 INFN-T1 switched to a custom solution the job accounting
In 2013 INFN-T1 switched to a custom solution for the job accounting
system~\cite{DGAS} based on a PostgreSQL backend. The database was
made more robust over time, introducing redundancy, reliable hardware
and storage. This architecture was powerful enough to also host other
......@@ -105,28 +132,28 @@ the AUGER experiment.
\subsection{Hardware setup}
A High Availability PostgreSQL instance has been deployed on two
identical SuperMicro hosts, ``dbfarm-1'' and ``dbfarm-2'' each one equipped as
identical SuperMicro hosts, ``dbfarm-1'' and ``dbfarm-2'', each one equipped as
follows:
\begin{itemize}
\item Intel(R) Xeon(R) CPU E5-2603 v2 @ 1.80GHz,
\item 32GB Ram
\item two FiberChannel controllers
\item a Storage Area Network volume of 2 TB
\item two redundant power supply
\item 32GB Ram,
\item two FiberChannel controllers,
\item a Storage Area Network volume of 2 TB,
\item two redundant power supply.
\end{itemize}
The path to the SAN storage is also fully redundant, since each Fiber Channel
controller is connected to two independent SAN switches.
One node also hosts 2 HDDs, 1.8TB configured with software RAID--1, to work as service storage
One node also hosts 2 HDDs ()1.8TB configured with software RAID-1) to work as service storage
area for supplementary data-base backup and other maintenance tasks.
\subsection{Software setup}
A PostgreSQL 11.1 master has been installed on the two host. dbfarm-1
has been set up to work as master and dbfarm-2 works as a Hot standby
replica. With this configuration the master is the main database,
while the replica can be accessed in read only mode. This instance is
A PostgreSQL 11.1 master has been installed on the two host; dbfarm-1
has been set up to work as master and dbfarm-2 works as a hot standby
replica. With this configuration, the master is the main database,
while the replica can be accessed in read-only mode. This instance is
used to host the accounting database of the farming, the inventory of
the hardware of the T1-centre (docet) and a database used by the CUPID
experiment. The content of this database is updated directly by
......@@ -135,7 +162,7 @@ nodes can access its data from the standby replica.
A second independent instance has also been installed on dbfarm-2
working as a hot standby replica of a remote Master instance managed
by the CUORE collaboration and located at INFN-LNGS. the continuous
by the CUORE collaboration and located at INFN-LNGS. The continuous
synchronization with the master database happens through a VPN channel.
Local read access from our Worker Nodes to this
instance can be quite intense: the standby server has been
......@@ -146,8 +173,8 @@ A different solution for the AUGER experiment has been put in place for several
years now, and has been recently redesigned when moving our Worker
Nodes to CentOS7. Several jobs of the Auger experiment need
concurrent read-only access to a MySQL (actually MariaDB, with CentOS7
and later) data base. A single server instance cannot sustain the
overall load generated by the clients. For this reason we have
and later) database. A single server instance cannot sustain the
overall load generated by the clients. For this reason, we have
configured a reasonable subset of Worker Nodes (two racks) to host a
local binary copy of the AUGER data base. The ``master'' copy of this database
is available from a dedicated User Interface and
......@@ -157,31 +184,32 @@ The copy on the Worker Nodes can be updated every few months, upon
request from the experiment. To do so, we must in order:
\begin{itemize}
\item drain any running job accessing the database
\item shutdown every MariaDB instance,
\item shutdown every MariaDB instance
\item update the binary copy using rsync
\item restart the database
\item re-enable normal auger activity
\item re-enable normal AUGER activity
\end{itemize}
\section{Helix Nebula Science Cloud}
During the first part of 2018, farming group has been directly involved in the pilot phase of Helix Nebula Science Cloud project~\cite{ref:hnsc}, whose aim was to allow research institutes like INFN to be able to test commercial clouds against HEP use-cases, identifying strength and weak points.
During the first part of 2018, the farming group has been directly involved in the pilot phase of Helix Nebula Science Cloud project~\cite{ref:hnsc}, whose aim was to allow research institutes like INFN to be able to test commercial clouds against HEP use-cases, identifying strength and weak points.
The pilot phase has seen some very intense interaction between the public procurers and both commercial and public service providers.
\subsection{Pilot Phase}
The pilot phase of the HNSciCloud PCP, is the final step in the implementation of the hybrid cloud platform proposed by the contractors that were selected. During the period January to June 2018, the technical activities of the project focused on
The pilot phase of the HNSciCloud PCP is the final step in the implementation of the hybrid cloud platform proposed by the contractors that were selected. During the period from January to June 2018, the technical activities of the project focused on
scalability of the platforms and on training of new users that will access the pilot at the end of this phase.
Farming members guided the contractors throughout the first part of the pilot phase,
testing the scalability of the proposed platforms, organizing the procurers’ hosted events and assessing the deliverables produced by the contractors together with the other partners of the project.
\subsection{Conclusions of the Pilot Phase}
Improvements to the platforms have been implemented during this phase even though
Improvements to the platforms have been implemented during this phase and even though
some R\&D activities had still to be completed, the general evaluation of the first part of the pilot phase is positive.
In particular, the Buyers Group reiterated the need for a fully functioning cloud storage service and highlighted the commercial advantage such a transparent data service represents for the Contractors. Coupled with a flexible voucher scheme, such an offering will encourage a greater uptake within the Buyers Group and the wider public research sector. The increase in demand for GPUs, even if not originally considered critical during the design phase, has become more important and highlighted a weak point in the current offering.
In particular, the Buyers Group reiterated the need for a fully functioning cloud storage service and highlighted the commercial advantage such a transparent data service represents for the Contractors. Coupled with a flexible voucher scheme, such an offering will encourage a greater uptake within the Buyers Group and the wider public research sector. The increase in demand for GPUs, even if not originally considered critical during the design phase, has become more important and highlighted a weak point in the current offer.
\section{References}
\begin{thebibliography}{9}
\bibitem{ref:cineca} Cineca webpage: https://www.cineca.it/
\bibitem{ref:ar17farming} Chierici A. et al. 2017 INFN-CNAF Annual Report 2017, edited by L. dell’Agnello, L. Morganti, and E. Ronchieri, pp. 111
\bibitem{ref:phedex} PhEDEx webpage: https://cmsweb.cern.ch/phedex/about.html
\bibitem{ref:singu} Singularity website: https://singularity.lbl.gov/
\bibitem{ref:meltdown} Meltdown attack website: https://meltdownattack.com/
......
contributions/fermi/fermi.tex
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......@@ -6,12 +6,12 @@
\title{The \Fermi-LAT experiment}
\author{
M Kuss$^{1}$,
F Longo$^{2}$,
M. Kuss$^{1}$,
F. Longo$^{2}$,
on behalf of the \Fermi LAT collaboration}
\address{$^{1}$ Istituto Nazionale di Fisica Nucleare, Sezione di Pisa, I-56127 Pisa, Italy}
\address{$^{2}$ Department of Physics, University of Trieste, via Valerio 2, Trieste and INFN, Sezione di Trieste, via Valerio 2, Trieste, Italy}
\address{$^{1}$ INFN Sezione di Pisa, Pisa, IT}
\address{$^{2}$ University of Trieste and INFN Sezione di Trieste, Trieste, IT}
\ead{michael.kuss@pi.infn.it}
\begin{abstract}
......
contributions/gamma/gamma.tex
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......@@ -28,7 +28,7 @@
\section{The GAMMA experiment and the AGATA array}
The strong interaction described by quantum chromodynamics (QCD) is responsible for binding neutrons and protons into nuclei and for the many facets of nuclear structure and reaction physics. Combined with the electroweak interaction, it determines the properties of all nuclei in a similar way as quantum electrodynamics shapes the periodic table of elements. While the latter is well understood, it is still unclear how the nuclear chart emerges from the underlying strong interactions. This requires the development of a unified description of all nuclei based on systematic theories of strong interactions at low energies, advanced few- and many-body methods, as well as a consistent description of nuclear reactions. Nuclear structure and dynamics have not reached the discovery frontier yet (e.g., new isotopes, new elements, …), and a high precision frontier is also being approached with higher beam intensities and purity, along with better efficiency and sensitivity of instruments. The access to new and complementary experiments combined with theoretical advances allows key questions to be addressed such as:
The strong interaction described by quantum chromodynamics (QCD) is responsible for binding neutrons and protons into nuclei and for the many facets of nuclear structure and reaction physics. Combined with the electroweak interaction, it determines the properties of all nuclei in a similar way as quantum electrodynamics shapes the periodic table of elements. While the latter is well understood, it is still unclear how the nuclear chart emerges from the underlying strong interactions. This requires the development of a unified description of all nuclei based on systematic theories of strong interactions at low energies, advanced few- and many-body methods, as well as a consistent description of nuclear reactions. Nuclear structure and dynamics have not reached the discovery frontier yet (e.g. new isotopes, new elements, …), and a high precision frontier is also being approached with higher beam intensities and purity, along with better efficiency and sensitivity of instruments. The access to new and complementary experiments combined with theoretical advances allows key questions to be addressed such as:
How does the nuclear chart emerge from the underlying fundamental interactions?
......@@ -51,8 +51,17 @@ What is the density and isospin dependence of the nuclear equation of state?
\noindent AGATA \cite{ref:gamma_first,ref:gamma_second} is the European Advanced Gamma Tracking Array for nuclear spectroscopy project consisting of a full shell of high purity segmented germanium detectors. Being fully instrumented with digital electronics it exploits the novel technique of gamma-ray tracking. AGATA will be employed at all the large-scale radioactive and stable beam facilities and in the long-term will be fully completed in 60 detectors unit geometry, in order to realize the envisaged scientific program. AGATA is being realized in phases with the goal of completing the first phase with 20 units by 2020. AGATA has been successfully operated since 2009 at LNL, GSI and GANIL, taking advantage of different beams and powerful ancillary detector systems. It will be used in LNL again in 2022, with stable beams and later with SPES radioactive beams, and in future years is planned to be installed in GSI/FAIR, Jyvaskyla, GANIL again, and HIE-ISOLDE.
\section{AGATA computing model and the role of CNAF}
At present the array consists of 15 units, each composed by a cluster of 3 HPGe crystals. Each individual crystal is composed of 36 segments for a total of 38 associated electronics channels/crystal. The data acquisition rate, including Pulse Shape Analysis, can stand up to 4/5 kHz events per crystal. The bottleneck is presently the Pulse Shape Analysis procedure to extract the interaction positions from the HPGe detectors traces. With future faster processor one expects to be able to process the PSA at 10 kHz/crystal. The amount of raw data per experiment, including traces, is about 20 TB for a standard data taking of about 1 week and can increase to 50 TB for specific experimental configuration. The collaboration is thus acquiring locally about 250 TB of data per year. During data-taking raw data is temporarily stored in a computer farm located at the experimental site and, later on, it is dispatched on the GRID in two different centers, CCIN2P3 (Lyon) and CNAF (INFN Bologna), used as TIER1: the duplication process is a security in case of failures/losses of one of the TIER1.
The GRID itself is seldom used to re-process the data and the users usually download their data set to local storage where they can run emulators able to manage part or the full workflow.
At present the array consists of 15 units, each composed by a cluster of 3 HPGe crystals.
Each individual crystal is composed of 36 segments for a total of 38 associated electronics channels/crystal.
The data acquisition rate, including Pulse Shape Analysis, can stand up to 4/5 kHz events per crystal.
The bottleneck is presently the Pulse Shape Analysis procedure to extract the interaction positions from the HPGe detectors traces.
With future faster processor one expects to be able to process the PSA at 10 kHz/crystal. The amount of raw data per experiment, including traces,
is about 20 TB for a standard data taking of about 1 week and can increase to 50 TB for specific experimental configuration.
The collaboration is thus acquiring locally about 250 TB of data per year. During data-taking raw data is temporarily stored
in a computer farm located at the experimental site and, later on, it is dispatched on the GRID in two different centers, CCIN2P3 (Lyon) and CNAF (INFN Bologna),
used as Tier 1: the duplication process is a security in case of failures/losses of one of the Tier 1 sites.
The GRID itself is seldom used to re-process the data and the users usually download their data set to local storage
where they can run emulators able to manage part or the full workflow.
\section{References}
......
contributions/icarus/report_2018.tex
View file @ 4db4fefd
......@@ -5,8 +5,8 @@
\begin{document}
\title{ICARUS}
\author{A. Rappoldi, on behalf of the ICARUS Collaboration}
\address{INFN, Sez. di Pavia, via Bassi, 6, 27100 Pavia, Italy}
\author{A. Rappoldi$^1$, on behalf of the ICARUS Collaboration}
\address{$^1$ INFN Sezione di Pavia, Pavia, IT}
\ead{andrea.rappoldi@pv.infn.it}
......@@ -20,13 +20,13 @@ Short Baseline Neutrino Project (SBN).
Indeed, the ICARUS T600 detector, which has undergone various technical upgrades
operations at CERN to improve its performance and make it more suitable
to operate at shallow depth, will constitute one of three LAr detectors
to operate at shallow depth, will constitute one of three Liquid Argon (LAr) detectors
exposed to the FNAL Booster Neutrino Beam (BNB).
The purpose of this project is to provide adequate answers to the
"sterile neutrino puzzle", due to the observation, claimed by various
``sterile neutrino puzzle'', due to the observation, claimed by various
other experiments, of anomalies in the results obtained in the
measurement of the parameters that regulate the mechansm of neutrino
measurement of the parameters that regulate the mechanism of neutrino
flavor oscillations.
\end{abstract}
......@@ -210,11 +210,11 @@ is scheduled for the 2019.
All the data (raw and reduced) will be stored on the Fermilab using local facility;
however, the ICARUS collaboration agreed to have a mirror site in Italy
(located at CNAF INFN Tier1) where to retain a full replica of the preselected
(located at CNAF INFN Tier 1) where to retain a full replica of the preselected
raw data, both to have redundancy and provide a more direct data access
to european part of the collaboration.
The CNAF Tier-1 computing resources assigned to ICARUS for 2018 consist of:
The CNAF Tier 1 computing resources assigned to ICARUS for 2018 consist of:
4000 HSPEC of CPU, 500 TB of disk storage and 1500 TB of tape archive.
A small fraction of the available storage has been used to
......@@ -225,7 +225,7 @@ During 2018 the ICARUS T600 detector was still in preparation, so
only a limited fraction
of such resorces has been used, mainly to perform data transfer tests
(from FNAL to CNAF) and to check the installation of LArSoft framework
in the Tier-1 environment. For this last purpose, a dedicate virtual
in the Tier 1 environment. For this last purpose, a dedicate virtual
machine with custom environment was also used.
......
contributions/juno/.gitkeep 0 → 100644
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contributions/juno/juno-annual-report-2019.pdf 0 → 100644
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contributions/km3net/km3net.tex
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......@@ -6,13 +6,13 @@
\author{C. Bozza$^1$, T. Chiarusi$^2$, K. Graf$^3$, A. Martini$^4$ for the KM3NeT Collaboration}
\address{$ˆ1$ Department of Physics of the University of Salerno and INFN Gruppo Collegato di Salerno, via Giovanni Paolo II 132, 84084 Fisciano, Italy}
\address{$ˆ1$ University of Salerno and INFN Gruppo Collegato di Salerno, Fisciano (SA), IT}
\address{$ˆ2$ INFN, Sezione di Bologna, v.le C. Berti-Pichat, 6/2, Bologna 40127, Italy}
\address{$ˆ2$ INFN Sezione di Bologna, Bologna, IT}
\address{$ˆ3$ Friedrich-Alexander-Universit{\"a}t Erlangen-N{\"u}rnberg, Erlangen Centre for Astroparticle Physics, Erwin-Rommel-Stra{\ss}e 1, 91058 Erlangen, Germany}
\address{$ˆ3$ Friedrich-Alexander-Universit{\"a}t Erlangen-N{\"u}rnberg, Erlangen, GE}
\address{$ˆ4$ INFN, LNF, Via Enrico Fermi, 40, Frascati, 00044 Italy}
\address{$ˆ4$ INFN-LNF, Frascati, IT}
\ead{cbozza@unisa.it}
......@@ -24,7 +24,7 @@ from astrophysical sources; the ORCA programme is devoted to
investigate the ordering of neutrino mass eigenstates. The
unprecedented size of detectors will imply PByte-scale datasets and
calls for large computing facilities and high-performance data
centres. The data management and processing challenges of KM3NeT are
centers. The data management and processing challenges of KM3NeT are
reviewed as well as the computing model. Specific attention is given
to describing the role and contributions of CNAF.
\end{abstract}
......@@ -80,7 +80,7 @@ way. One ORCA DU was also deployed and operated in 2017, with smooth
data flow and processing. At present time, most of the computing load is
due to simulations for the full building block, now being enriched with
feedback from real data analysis. As a first step, this
was done at CC-IN2P3 in Lyon, but usage of other computing centres is
was done at CC-IN2P3 in Lyon, but usage of other computing centers is
increasing and is expected to soon spread to the full KM3NeT
computing landscape. This process is being driven in accordance to the
goals envisaged in setting up the computing model. The KM3NeT
......@@ -105,14 +105,14 @@ flow with a reduction from $5 GB/s$ to $5 MB/s$ per \emph{building
block}. Quasi-on-line reconstruction is performed for selected
events (alerts, monitoring). The output data are temporarily stored on
a persistent medium and distributed with fixed latency (typically less
than few hours) to various computing centres, which altogether
than few hours) to various computing centers, which altogether
constitute Tier 1, where events are reconstructed by various fitting
models (mostly searching for shower-like or track-like
patterns). Reconstruction further reduces the data rate to about $1
MB/s$ per \emph{building block}. In addition, Tier 1 also takes care
of continuous detector calibration, to optimise pointing accuracy (by
working out the detector shape that changes because of water currents)
and photomultiplier operation. Local analysis centres, logically
and photomultiplier operation. Local analysis centers, logically
allocated in Tier 2 of the computing model, perform physics analysis
tasks. A database system interconnects the three tiers by distributing
detector structure, qualification and calibration data, run
......@@ -124,10 +124,10 @@ book-keeping information, and slow-control and monitoring data.
\label{fig:compmodel}
\end{figure}
KM3NeT exploits computing resources in several centres and in the
KM3NeT exploits computing resources in several centers and in the
GRID, as sketched in Fig.~\ref{fig:compmodel}. The conceptually simple
flow of the three-tier model is then realised by splitting the tasks
of Tier 1 to different processing centres, also optimising the data
of Tier 1 to different processing centers, also optimising the data
flow and the network path. In particular, CNAF and CC-IN2P3 aim at being
mirrors of each other, containing the full data set at any moment. The
implementation for the data transfer from CC-IN2P3 to CNAF (via an
......@@ -144,9 +144,9 @@ for a while becuse of the lack of human resources.
\section{Data size and CPU requirements}
Calibration and reconstruction work in batches. The raw data related
to the batch are transferred to the centre that is in charge of the
to the batch are transferred to the center that is in charge of the
processing before it starts. In addition, a rolling buffer of data is
stored at each computing centre, e.g.\ the last year of data taking.
stored at each computing center, e.g.\ the last year of data taking.
Simulation has special needs because the input is negligible, but the
computing power required is very large compared to the needs of
......@@ -179,9 +179,8 @@ Thanks to the modular design of the detector, it is possible to quote
the computing requirements of KM3NeT per \emph{building block}, having
in mind that the ARCA programme corresponds to two \emph{building
blocks} and ORCA to one. Not all software could be benchmarked, and
some estimates are derived by scaling from ANTARES ones. When needed,
a conversion factor about 10 between cores and HEPSpec2006 (HS06) is
used in the following.
some estimates are derived by scaling from ANTARES ones.
In the following, the standard conversion factor (~10) is used between cores and HEPSpec2006 (HS06).
\begin{table}
\caption{\label{cpu}Yearly resource requirements per \emph{building block}.}
......@@ -211,7 +210,7 @@ resources at CNAF has been so far below the figures for a
units are added in the following years. KM3NeT software that
runs on the GRID can use CNAF computing nodes in opportunistic mode.
Already now, the data handling policy to safeguard the products of Tier-0
Already now, the data handling policy to safeguard the products of Tier 0
is in place. Automatic synchronization from each shore station to both
CC-IN2P3 and CNAF runs daily and provides two maximally separated
paths from the data production site to final storage places. Mirroring
......@@ -219,11 +218,11 @@ and redundancy preservation between CC-IN2P3 and CNAF are foreseen and
currently at an early stage.
CNAF has already added relevant contributions to KM3NeT in terms of
know-how for IT solution deployment, e.g.~the above-mentioned synchronisation, software development solutions and the software-defined network at the Tier-0 at
know-how for IT solution deployment, e.g.~the above-mentioned synchronisation, software development solutions and the software-defined network at the Tier 0 at
the Italian site. Setting up Software Defined Networks (SDN) for data
acquisition deserves a special mention. The SDN technology\cite{SDN} is used to
configure and operate the mission-critical fabric of switches/routers
that interconnects all the on-shore resources in Tier-0 stations. The
that interconnects all the on-shore resources in Tier 0 stations. The
KM3NeT DAQ is built around switches compliant with the OpenFlow 1.3
protocol and managed by dedicated controller servers. With a limited
number of Layer-2 forwarding rules, developed on purpose for the KM3NeT
......
contributions/lhcb/lhcb.tex
View file @ 4db4fefd
......@@ -3,20 +3,17 @@
\begin{document}
\title{LHCb Computing at CNAF}
\author{Stefano Perazzini}
\author{S. Perazzini$^1$, C. Bozzi$^{2,3}$}
\address{INFN Sezione di Bologna, viale Berti Pichat 6/2, 40127 Bologna (BO), Italy E-mail: Stefano.Perazzini@bo.infn.it}
\address{$^1$ INFN Sezione di Bologna, Bologna, IT}
\address{$^2$ CERN, Gen\`eve, CH}
\address{$^3$ INFN Sezione di Ferrara, Ferrara, IT}
\author{Concezio Bozzi}
\address{CERN, EP/LBD, CH-1211 Geneve 23, Switzerland, and INFN Sezione di Ferrara, via Saragat 1, 44122 Ferrara, Italy E-mail: Concezio.Bozzi@fe.infn.it}
\ead{bozzi@fe.infn.it}
\ead{stefano.perazzini@bo.infn.it, concezio.bozzi@fe.infn.it}
\begin{abstract}
In this document a summary of the LHCb computing activities during the 2018 is reported. The usage of the CPU, disk and tape resources spread among various computing centres is analysed, with particular attention to the performances of the INFN Tier 1 at CNAF. Projections of the necessary resources in the years to come are also briefly discussed.
In this document a summary of the LHCb computing activities during the 2018 is reported. The usage of the CPU, disk and tape resources spread among various computing centers is analysed, with particular attention to the performances of the INFN Tier 1 at CNAF. Projections of the necessary resources in the years to come are also briefly discussed.
\end{abstract}
\section{Introduction}
......@@ -44,7 +41,7 @@ The offline reconstruction of the FULL stream for proton collision data run from
A full re-stripping of 2015, 2016 and 2017 proton collision data, started in autumn 2017, ended in April 2018. A stripping cycle of 2015 lead collision data was also performed in that period. The stripping cycle concurrent with the 2018 proton collision data taking started in June and run continuously until November.
The INFN Tier1 centre at CNAF was in downtime from November 2017, due to a major flood incident. However, the site was again fully available in March 2018, allowing the completion of the stripping cycles on hold, waiting for the data located at CNAF (about 20\% of the total). Despite the unavailability of CNAF resources for the first months of 2018 the site performed excellently for the rest of the year, as testified by the number reported in this report.
The INFN Tier 1 center at CNAF was in downtime from November 2017, due to a major flood incident. However, the site was again fully available in March 2018, allowing the completion of the stripping cycles on hold, waiting for the data located at CNAF (about 20\% of the total). Despite the unavailability of CNAF resources for the first months of 2018 the site performed excellently for the rest of the year, as testified by the number reported in this report.
As in previous years, LHCb continued to make use of opportunistic resources, that are not pledged to WLCG, but that significantly contributed to the overall usage.
......@@ -67,27 +64,27 @@ Total WLCG & 502 & 41.3 & 90.5\\ \hline
\label{tab:pledges}
\end{table}
The usage of WLCG CPU resources by LHCb is obtained from the different views provided by the EGI Accounting portal. The CPU usage is presented in Figure~\ref{fig:T0T1} for the Tier0 and Tier1s and in Figure~\ref{fig:T2} for Tier2s . The same data is presented in tabular form in Table~\ref{tab:T0T1} and Table~\ref{tab:T2}, respectively.
The usage of WLCG CPU resources by LHCb is obtained from the different views provided by the EGI Accounting portal. The CPU usage is presented in Figure~\ref{fig:T0T1} for the Tier 0 and Tier 1 sites and in Figure~\ref{fig:T2} for Tier 2 sites. The same data is presented in tabular form in Table~\ref{tab:T0T1} and Table~\ref{tab:T2}, respectively.
\begin{figure}
\begin{center}
\includegraphics[width=0.8\textwidth]{T0T1.png}
\end{center}
\caption{\label{fig:T0T1}Monthly CPU work provided by the Tier-0 and
Tier 1 centres to LHCb during 2018.}
\caption{\label{fig:T0T1}Monthly CPU work provided by the Tier 0 and
Tier 1 centers to LHCb during 2018.}
\end{figure}
\begin{figure}
\begin{center}
\includegraphics[width=0.8\textwidth]{T2.png}
\end{center}
\caption{\label{fig:T2}Monthly CPU work provided by the Tier-2 centres to LHCb during 2018.}
\caption{\label{fig:T2}Monthly CPU work provided by the Tier 2 centers to LHCb during 2018.}
\end{figure}
\begin{table}[htbp]
\caption{Average CPU power provided by the Tier-0 and the Tier 1
centres to LHCb during 2018.}
\caption{Average CPU power provided by the Tier 0 and the Tier 1
centers to LHCb during 2018.}
\centering
\begin{tabular}{lcc}
\hline
......@@ -110,8 +107,8 @@ UK-T1-RAL & 71.7 & 74.8 \\
\end{table}
\begin{table}[htbp]
\caption{Average CPU power provided by the Tier-2
centres to LHCb during 2018.}
\caption{Average CPU power provided by the Tier 2
centers to LHCb during 2018.}
\centering
\begin{tabular}{lcc}
\hline
......@@ -137,21 +134,21 @@ UK & 85.7 & 29.3 \\
\label{tab:T2}
\end{table}
The average power used at Tier0+Tier1s sites is about 32\% higher than the pledges. The average power used at Tier2s is about 26\% higher than the pledges.
The average power used at Tier 0 + Tier 1 sites is about 32\% higher than the pledges. The average power used at Tier 2 sites is about 26\% higher than the pledges.
The average CPU power accounted for by WLCG (including Tier0/1 + Tier2) amounts to 654 kHS06, to be compared to 502 kHS06 estimated needs quoted in Table~\ref{tab:pledges}. The Tier0 and Tier1s usage is generally higher than the pledges. The LHCb computing model is flexible enough to use computing resources for all production workflows wherever available. It is important to note that this is true also for CNAF, despite it started to contribute to the computing activities only in March, after the recovery from the incident. After that the CNAF Tier1 has offered great stability, leading to maximal efficiency in the overall exploitation of the resources. The total amount of CPU used at Tier0 and Tier1s centres is detailed in Figure~\ref{fig:T0T1_MC}, showing that about 76\% of the CPU work is due to Monte Carlo simulation. From the same plot it is visible the start of a stripping campaign in March. This corresponds to the recovery of the backlog in the restripping of the Run2 data collected in 2015-2017, due to the unavailability of CNAF after the incident of November 2017. As it is visible from the plot, the backlog has been recovered by the end of April 2018, before the restart of data-taking operations. Even if all the other Tier1s contributed to reprocess these data, the recall of them from tape has been done exclusively at CNAF. Approximately 580 TB of data have been recalled from tape in about 6 weeks, with a maximum throughput of about 250 MB/s.
The average CPU power accounted for by WLCG (including Tier 0/1 + Tier 2) amounts to 654 kHS06, to be compared to 502 kHS06 estimated needs quoted in Table~\ref{tab:pledges}. The Tier 0 and Tier 1s usage is generally higher than the pledges. The LHCb computing model is flexible enough to use computing resources for all production workflows wherever available. It is important to note that this is true also for CNAF, despite it started to contribute to the computing activities only in March, after the recovery from the incident. After that the CNAF Tier 1 has offered great stability, leading to maximal efficiency in the overall exploitation of the resources. The total amount of CPU used at Tier 0 and Tier 1s centers is detailed in Figure~\ref{fig:T0T1_MC}, showing that about 76\% of the CPU work is due to Monte Carlo simulation. From the same plot it is visible the start of a stripping campaign in March. This corresponds to the recovery of the backlog in the restripping of the Run2 data collected in 2015-2017, due to the unavailability of CNAF after the incident of November 2017. As it is visible from the plot, the backlog has been recovered by the end of April 2018, before the restart of data-taking operations. Even if all the other Tier 1 centers contributed to reprocess these data, the recall of them from tape has been done exclusively at CNAF. Approximately 580 TB of data have been recalled from tape in about 6 weeks, with a maximum throughput of about 250 MB/s.
\begin{figure}
\begin{center}
\includegraphics[width=0.8\textwidth]{T0T1_MC.png}
\end{center}
\caption{\label{fig:T0T1_MC}Usage of LHCb resources at Tier0 and Tier1s during 2018. The plot shows the normalized CPU usage (kHS06) for the various activities.}
\caption{\label{fig:T0T1_MC}Usage of LHCb resources at Tier 0 and Tier 1 sites during 2018. The plot shows the normalized CPU usage (kHS06) for the various activities.}
\end{figure}
Since the start of data taking in May 2018, tape storage grew by about 16.7 PB. Of these, 9.5 PB were due to new collected RAW data. The rest was due to RDST (2.6 PB) and ARCHIVE (4.6 PB), the latter due to the archival of Monte Carlo productions, re-stripping of former real data, and new Run2 data. The total tape occupancy as of December 31st 2018 is 68.9 PB, 38.4 PB of which are used for RAW data, 13.3 PB for RDST, 17.2 PB for archived data. This is 12.9\% lower than the original request of 79.2 PB. The total tape occupancy at CNAF at the end of 2018 was about 9.3 PB, of which 3.3 PB of RAW data, 3.6 PB of ARCHIVE and 2.4 of RDST. This correspond to an increase of about 2.3 PB with respect to the end of 2017. These numbers are in agreement with the share of resources expected from CNAF.
\begin{table}[htbp]
\caption{Disk Storage resource usage as of February 11$^{\rm th}$ 2019 for the Tier0 and Tier1s centres. The top row is taken from the LHCb accounting, the other ones (used, available and installed capacity) are taken from the recently commissioned WLCG Storage Space Accounting tool. The 2018 pledges are shown in the last row.}
\caption{Disk Storage resource usage as of February 11$^{\rm th}$ 2019 for the Tier 0 and Tier 1 centers. The top row is taken from the LHCb accounting, the other ones (used, available and installed capacity) are taken from the recently commissioned WLCG Storage Space Accounting tool. The 2018 pledges are shown in the last row.}
\begin{center}
\resizebox{\columnwidth}{!}{
\begin{tabular}{|l|cc|ccccccc|}
......@@ -173,14 +170,14 @@ Pledge '18 & 11.4 & 26.25 & 5.61 & 4.01 & 3.20 & 1.43 & 7.32
\end{center}
\end{table}
Table~\ref{tab:disk} shows the situation of disk storage resources at CERN and Tier1s, as well as at each Tier1 site, as of February 11$^{\rm th}$ 2019. The used space includes derived data, i.e. DST and micro-DST of both real and simulated data, and space reserved for users. The latter accounts for 1.2 PB in total, 0.9 of which are used. The SRR disk used and SRR disk free information concerns only permanent disk storage (previously known as “T0D1”). The first two lines show a good agreement between what the site reports and what the LHCb accounting (first line) reports. The sum of the Tier0 and Tier1s 2018 pledges amount to 37.7 PB. The available disk space is 35 PB in total, 26 PB of which are used to store real and simulated datasets, and user data. A total of 3.7PB is used as tape buffer, the remaining 5 PB are free and will be used to store the output of the legacy stripping campaigns of Run1 and Run2 data that are currently being prepared. The disk space available at CNAF is about 6.6 PB, about 18\% above the pledge.
Table~\ref{tab:disk} shows the situation of disk storage resources at CERN and Tier 1 sites, as well as at each Tier 1 site, as of February 11$^{\rm th}$ 2019. The used space includes derived data, i.e. DST and micro-DST of both real and simulated data, and space reserved for users. The latter accounts for 1.2 PB in total, 0.9 of which are used. The SRR disk used and SRR disk free information concerns only permanent disk storage (previously known as “T0D1”). The first two lines show a good agreement between what the site reports and what the LHCb accounting (first line) reports. The sum of the Tier 0 and Tier 1 sites 2018 pledges amount to 37.7 PB. The available disk space is 35 PB in total, 26 PB of which are used to store real and simulated datasets, and user data. A total of 3.7 PB is used as tape buffer, the remaining 5 PB are free and will be used to store the output of the legacy stripping campaigns of Run1 and Run2 data that are currently being prepared. The disk space available at CNAF is about 6.6 PB, about 18\% above the pledge.
In summary, the usage of computing resources in the 2018 calendar year has been quite smooth for LHCb. Simulation is the dominant activity in terms of CPU work. Additional unpledged resources, as well as clouds, on-demand and volunteer computing resources, were also successfully used. They were essential
in providing CPU work during the outage of the CNAF Tier 1 centre. As for the INFN Tier1 at CNAF, it came back to its fully-operational status in March 2018. After that, the backlog in the restripping campaign due to unavailability of data stored at CNAF was recovered, thanks also to the contribution of other sites, in time for the restart of data taking. After March 2018, CNAF operated in a very efficient and reliable way, being even able to over perform in terms of CPU power with respect to the pledged resources.
in providing CPU work during the outage of the CNAF Tier 1 center. As for the INFN Tier 1 at CNAF, it came back to its fully-operational status in March 2018. After that, the backlog in the restripping campaign due to unavailability of data stored at CNAF was recovered, thanks also to the contribution of other sites, in time for the restart of data taking. After March 2018, CNAF operated in a very efficient and reliable way, being even able to over perform in terms of CPU power with respect to the pledged resources.
\section{Expected growth of resources in 2020-2021}
In terms of CPU requirements, the different activities result in CPU work estimates for 2020-2021, that are apportioned between the different Tiers taking into account the computing model constraints and also capacities that are already installed. This results in the requests shown in Table~\ref{tab:req_CPU} together with the pledged resources for 2019. The CPU work required at CNAF would correspond to about 18\% of the total CPU requested at Tier1s+Tier2s sites.
In terms of CPU requirements, the different activities result in CPU work estimates for 2020-2021, that are apportioned between the different Tiers taking into account the computing model constraints and also capacities that are already installed. This results in the requests shown in Table~\ref{tab:req_CPU} together with the pledged resources for 2019. The CPU work required at CNAF would correspond to about 18\% of the total CPU requested at Tier 1s+Tier 2s sites.
\begin{table}[htbp]
\centering
\caption{CPU power requested at the different Tiers in 2020-2021. Pledged resources for 2019 are also reported}
......@@ -198,7 +195,7 @@ In terms of CPU requirements, the different activities result in CPU work estima
\end{tabular}
\end{table}
The forecast total disk and tape space usage at the end of the years 2019-2020 are broken down into fractions to be provided by the different Tiers. These numbers are shown in Table~\ref{tab:req_disk} for disk and Table~\ref{tab:req_tape} for tape. The disk resources required at CNAF would be about 18\% of those requested for Tier1s+Tier2s sites, while for tape storage CNAF is supposed to provide about 24\% of the total tape request to Tier1s sites.
The forecast total disk and tape space usage at the end of the years 2019-2020 are broken down into fractions to be provided by the different Tiers. These numbers are shown in Table~\ref{tab:req_disk} for disk and Table~\ref{tab:req_tape} for tape. The disk resources required at CNAF would be about 18\% of those requested for Tier 1 sites + Tier 2 sites, while for tape storage CNAF is supposed to provide about 24\% of the total tape request to Tier 1 sites.
\begin{table}[htbp]
\centering
......@@ -208,11 +205,11 @@ The forecast total disk and tape space usage at the end of the years 2019-2020 a
\hline
Disk (PB) & 2019 & 2020 & 2021 \\
\hline
Tier0 & 13.4 & 17.2 & 19.5 \\
Tier 0 & 13.4 & 17.2 & 19.5 \\
Tier 1 & 29.0 & 33.2 & 39.0 \\
Tier2 & 4 & 7.2 & 7.5 \\
Tier 2 & 4 & 7.2 & 7.5 \\
\hline
Total & 46.4 & 57.6 & 66.0 \\
Total WLCG & 46.4 & 57.6 & 66.0 \\
\hline
\end{tabular}
\end{table}
......@@ -225,16 +222,16 @@ The forecast total disk and tape space usage at the end of the years 2019-2020 a
\hline
Tape (PB) & 2019 & 2020 & 2021 \\
\hline
Tier0 & 35.0 & 36.1 & 52.0 \\
Tier 0 & 35.0 & 36.1 & 52.0 \\
Tier 1 & 53.1 & 55.5 & 90.0 \\
\hline
Total & 88.1 & 91.6 & 142.0 \\
Total WLCG & 88.1 & 91.6 & 142.0 \\
\hline
\end{tabular}
\end{table}
\section{Conclusion}
A description of the LHCb computing activities during 2018 has been given, with particular emphasis on the usage of resources and on the forecasts of resource needs until 2021. As in previous years, the CNAF Tier1 centre gave a substantial contribution to LHCb computing in terms of CPU work and storage made available to the collaboration. This achievement is particularly important this year, as CNAF was recovering from the major incident of November 2017 that unfortunately interrupted its activities. The effects of CNAF unavailability have been overcome also thanks to extra efforts from other sites and to the opportunistic usage of non-WLCG resources. The main consequence of the incident, in terms of LHCb operations, has been the delay in the restripping campaign of data collected during 2015-2017. The data that were stored at CNAF (approximately 20\% of the total) have been processed when the site restarted the operations in March 2018. It is worth to mention that despite the delay, the restripping campaign has been completed before the start of data taking according to the predicted schedule, avoiding further stress to the LHCb computing operations. Emphasis should be put also on the fact that an almost negligible amount of data have been lost in the incident and in any case it has been possible to recover them from backup copies stored at other sites.
A description of the LHCb computing activities during 2018 has been given, with particular emphasis on the usage of resources and on the forecasts of resource needs until 2021. As in previous years, the CNAF Tier 1 center gave a substantial contribution to LHCb computing in terms of CPU work and storage made available to the collaboration. This achievement is particularly important this year, as CNAF was recovering from the major incident of November 2017 that unfortunately interrupted its activities. The effects of CNAF unavailability have been overcome also thanks to extra efforts from other sites and to the opportunistic usage of non-WLCG resources. The main consequence of the incident, in terms of LHCb operations, has been the delay in the restripping campaign of data collected during 2015-2017. The data that were stored at CNAF (approximately 20\% of the total) have been processed when the site restarted the operations in March 2018. It is worth to mention that despite the delay, the restripping campaign has been completed before the start of data taking according to the predicted schedule, avoiding further stress to the LHCb computing operations. Emphasis should be put also on the fact that an almost negligible amount of data have been lost in the incident and in any case it has been possible to recover them from backup copies stored at other sites.
\end{document}
contributions/lhcf/lhcf.tex
View file @ 4db4fefd
......@@ -26,7 +26,7 @@ The LHCf detector is made of two independent electromagnetic calorimeters placed
\section{Results obtained in 2018}
During 2018 no experimental operations were performed in LHC tunnel or SPS experimental area, so all the work was concentrated to the analysis of data collected during the 2015 operation in p-p collisions at 13 TeV and during 2016 operation in p-Pb collisions at 8.16 TeV.
The final results of photon and neutron production spectra in proton-proton collisions at $\sqrt{s} =$ 13 TeV in the very forward region ($8.81 < \eta < 8.99$ and $\eta > 10.94$ for photons, $8.81 < \eta < 9.22$ and $\eta > 10.76$ for neutrons) were published on Physics Letters B and Journal of High Energy Physics, respectively \cite{LHCf_photons, LHCf_neutrons}.
The final results of photon and neutron production spectra in proton-proton collisions at $\sqrt{s} =$ 13 TeV in the very forward region ($8.81 < \eta < 8.99$ and $\eta > 10.94$ for photons, $8.81 < \eta < 9.22$ and $\eta > 10.76$ for neutrons, where $\eta$ is the pseudorapidity of the particle\footnote{In accelerator experiments the pseudorapidity of a particle is defined as $\eta = - \ln [ \tan(\theta / 2) ]$, where $\theta$ is the angle between the particle momentum and the beam axis.}) were published on Physics Letters B and Journal of High Energy Physics, respectively \cite{LHCf_photons, LHCf_neutrons}.
These are the first published results of the collaboration at the highest available collision energy of 13 TeV at the LHC.
In addition to proton-proton results, preliminary results for photon spectrum in proton-lead collisions at $\sqrt{s_{NN}} = 8.16$ TeV were obtained and presented in several international conferences.
......
contributions/limadou/limadou.tex
View file @ 4db4fefd
......@@ -3,9 +3,9 @@
\begin{document}
\title{CSES-Limadou at CNAF}
\author{Matteo Merg\'e}
\author{Matteo Merg\'e$^1$}
\address{Agenzia Spaziale Italiana, Space Science Data Center ASI-SSDC \newline via del politecnico 1, 00133, Rome, Italy }
\address{$^1$ Agenzia Spaziale Italiana, Space Science Data Center ASI-SSDC, Rome, IT}
\ead{matteo.merge@roma2.infn.it, matteo.merge@ssdc.asi.it}
......@@ -21,7 +21,7 @@ The High-Energy Particle Detector (HEPD), developed by the INFN, detects electro
The instrument consists of several detectors. Two planes of double-side silicon microstrip sensors placed on the top of the instrument provide the direction of the incident particle. Just below, two layers of plastic scintillators, one thin segmented, give the trigger; they are followed by a calorimeter, constituted by other 16 scintillators and a layer of LYSO sensors. A scintillator veto system completes the instrument.
\section{HEPD Data}
The reconstruction occurs in three phases, which determine three different data formats, namely 0, 1 and 2, with increasing degree of abstraction. This structure is reflected on the data-persistency format, as well as on the software design. Raw data as downlinked from the CSES. They include ADC counts from the silicon strip, detector, from trigger scintillators, from energy scintillators and from LYSO crystals. ADC counts from lateral veto are also there, together with other very low-level information. Data are usually stored in ROOT format. Level 1 data contain all detector responses after calibration and equalization. The tracker response is clustered (if not already in this format at level0) and corrected for the signal integration time. All scintillator responses are calibrated and equalized. Information on the event itself like time, trigger flags, dead/alive time, etc… are directly inherited from level 0. Data are usually stored in ROOT format. Level 2 data contain higher level information, used to compute final data products. Currently the data are transferred from China as soon as they are downlinked from the CSES satellite and are processed at a dedicated facility at ASI Space Science Data Center (ASI-SSDC \cite{ssdc}) and then distributed to the analysis sites includind CNAF.
The reconstruction occurs in three phases, which determine three different data formats, namely 0, 1 and 2, with increasing degree of abstraction. This structure is reflected on the data-persistency format, as well as on the software design. Raw data as downlinked from the CSES. They include ADC counts from the silicon strip, detector, from trigger scintillators, from energy scintillators and from LYSO crystals. ADC counts from lateral veto are also there, together with other very low-level information. Data are usually stored in ROOT format. Level 1 data contain all detector responses after calibration and equalization. The tracker response is clustered (if not already in this format at level0) and corrected for the signal integration time. All scintillator responses are calibrated and equalized. Information on the event itself like time, trigger flags, dead/alive time, etc… are directly inherited from level 0. Data are usually stored in ROOT format. Level 2 data contain higher level information, used to compute final data products. Currently the data are transferred from China as soon as they are downlinked from the CSES satellite and are processed at a dedicated facility at ASI Space Science Data Center (ASI-SSDC \cite{ssdc}) and then distributed to the analysis sites including CNAF.
\section{HEPD Data Analysis at CNAF}
Level2 data of the HEPD detector are currently produced daily in ROOT format from the raw files. Once a week they are transferred at CNAF, using gfal-tools for the analysis team to be used. Raw data are transfered also to the CNAF facility on weekly basis and will be transferred to the tape storage. Most of the data analysis software and tools have been developed to be used at CNAF. Geant4 MC simulations are currently ran at CNAF by the collaboration, the facility proved to be crucial to perform, computational intensive, optical photons simulations needed to simulate the light yield of the plastic scintillators of the detector. Most of the software is written in C++/ROOT while several attempts to use Machine Learning and Neural Networks tecniques are pushing the collaboration to use more frequently Python for the analysis.
......
contributions/na62/main.tex
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......@@ -14,12 +14,10 @@
\ead{antonino.sergi@cern.ch}
\begin{abstract}
The rare decays
are theoretically clean processes excellent to make tests of new
Rare decays are theoretically clean processes excellent to test new
physics at the highest scale complementary to LHC. The NA62 experiment at CERN SPS aims
to collect of the order of 100
events in two years of data taking, keeping the back-
ground less than 20\% of the signal.
events in two years of data taking, keeping the background lower than 20\% of the signal.
\end{abstract}
\section{Introduction}
......
contributions/net/main.tex
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\documentclass[a4paper]{jpconf}
\usepackage{graphicx}
\begin{document}
\title{The INFN-Tier1: Network and Security}
\title{The INFN-Tier 1: Network and Security}
\author{S.~Zani$^1$, D.~De~Girolamo$^1$, L.~Chiarelli$^{1,2}$, V.~Ciaschini$^1$}
\address{$^1$ INFN-CNAF, Bologna, IT}
......@@ -18,17 +17,22 @@
%\end{abstract}
\section{Introduction}
The Network unit manages the wide area and local area connections of CNAF, it is responsible for the security of the center, contributes to the management of the local CNAF services (e.g., DNS, Windows domain etc.) and some of the INFN national ICT services. It gives also support to the GARR PoP hosted at CNAF.
The Network unit manages the wide area and local area connections of CNAF.
Moreover, it is responsible for the security of the center, and it contributes to the management of the local CNAF services
(e.g. DNS, Windows domain etc.) and some of the INFN national ICT services. It gives also support to the GARR PoP hosted at CNAF.
\section{Wide Area Network}
Inside CNAF datacentre is hosted the main PoP of GARR network, based on a fully managed dark fiber infrastructure.
T he main PoP of GARR network, based on a fully managed dark fiber infrastructure, is hosted tnside CNAF data center.
CNAF is connected to the WAN via GARR/GEANT essentially with two physical links:
\begin{itemize}
\item General Internet: General IP link is $20 Gbps$ (2x10 Gbps) via GARR and GEANT
\item LHCOPN/LHCONE: The link to WLCG destinations is $200Gbps$ (2x100 Gbps) link shared between the LHC-OPN network for traffic with the Tier-0 (CERN) and the other Tier-1s and LHCONE network mainly for traffic with the Tier-2s. Since Summer 2018, the LHCOPN dedicated link to CERN (from Milan GARR POP) has been upgraded to 2x100 Gbps while the peering to LHCONE is at $100Gbps$ (from Milan GARR POP and GEANT GARR POP).
\item General Internet: General IP link is 20 Gbps (2x10 Gbps) via GARR and GEANT;
\item LHCOPN/LHCONE: The link to WLCG destinations is 200 Gbps (2x100 Gbps) link shared between the LHC-OPN network for traffic
with the Tier 0 (CERN) and the other Tier 1 sites and LHCONE network mainly for traffic with the Tier 2 centers.
Since summer 2018, the LHCOPN dedicated link to CERN (from Milan GARR POP) has been upgraded to 2x100 Gbps
while the peering to LHCONE is at 100 Gbps (from Milan GARR POP and GEANT GARR POP).
\end{itemize}
......@@ -36,13 +40,15 @@ CNAF is connected to the WAN via GARR/GEANT essentially with two physical links:
\begin{center}
\includegraphics[width=30pc]{connection-schema.png}\hspace{2pc}%
%\begin{minipage}[b]{14pc}
\caption{\label{schema-rete}INFN CNAF connection schema.}
\caption{\label{schema-rete}INFN-CNAF connection schema.}
%\end{minipage}
\end{center}
\end{figure}
As shown in the figures~\ref{lhc-opn-usage} and \ref{gpn-usage}, the network usage is growing both on LHCOPN/ONE and on General IP, even if, at the beginning of last year the traffic was very low because of the flooding occurred in November 2017 (the Computing Center returned completely online during February 2018).
As shown in Figures~\ref{lhc-opn-usage} and \ref{gpn-usage}, network usage is growing both on LHCOPN/ONE and on General IP,
even if, at the beginning of last year, the traffic was very low because of the flooding occurred in November 2017
(the Computing Center returned completely online during February 2018).
\begin{figure}[h]
......@@ -62,30 +68,37 @@ As shown in the figures~\ref{lhc-opn-usage} and \ref{gpn-usage}, the network usa
\end{figure}
Currently the dedicated bandwidth for LHCOPN to CERN is 100Gbps with a backup link of 4x10Gbps. During 2019 the configuration will change and there will be provided 2x100 Gb/s links to the two CERN POP granting a better resiliency and giving potentially 200 Gbpss full speed with CERN and the Tier-1s.
Currently the dedicated bandwidth for LHCOPN to CERN is 100 Gbps with a backup link of 4x10 Gbps.
During 2019, the configuration will change and 2x100 Gb/s links to the two CERN POP will be provided in order to grant a better resiliency
and to give potentially 200 Gbps full speed with CERN and the Tier 1s.
\section{Data Center Interconnect with CINECA}
At the beginning of the 2018, CNAF obtained by CINECA the use of 216 Servers based on Intel Xeon CPU E5-2697 v4 (with 36 physical cores) coming from the Super Computer “Marconi” partition 1 in phase out for HPC workflows.
At the beginning of 2018, CNAF obtained from CINECA the use of 216 Servers based on Intel Xeon CPU E5-2697 v4
(with 36 physical cores) coming from the Super Computer “Marconi” partition 1 in phase-out for HPC workflows.
In order to integrate all of those computing resources in our farm, it has been fundamental to guarantee the appropriate access bandwidth to the storage resources located at CNAF. This has been implemented with the collaboration of GARR using the Data Center Interconnect (DCI) technology
provided by a pair of Infinera Cloud Express 2 (CX1200).
The Cloud Express 2 are Transponders with 12 x 100 Gigabit Ethernet interfaces on LAN Side and one LC fiber interface on “Line” side capable of up to 1,2 Tbps on a single mode fiber at a maximum distance of 100 Kilometers (CNAF and CINECA are 17 km far). In CNAF-CINECA case, the systems are configured for a 400 Gbps connection.
The Cloud Express 2 are Transponders with 12 x 100 Gigabit Ethernet interfaces on LAN Side and one LC fiber interface on “Line” side capable of up to 1,2 Tbps on a single mode fiber at a maximum distance of 100 kilometers (CNAF and CINECA are 17 km far). In CNAF-CINECA case, the systems are configured for a 400 Gbps connection.
The latency introduced by each CX1200 is of $\sim 5 \mu$s and the total RTT (Round Trip Time) between servers at CNAF and servers at CINECA is of 0,48 ms comparable to what we observe on the LAN (0,28 ms).
The latency introduced by each CX1200 is of $\sim 5 \mu$s and the total RTT (Round Trip Time) between servers at CNAF and servers at CINECA is of 0,48 ms,
comparable to what we observe on the LAN (0,28 ms).
All worker nodes on the network segment at CINECA have IP addresses of the INFN Tier-1 network and are used as they were installed at the Tier-1 facility (see fig.~\ref{cineca-schema}). The data access bandwidth is 400 Gbps but can scale up to 1,2 Tbps.
All worker nodes on the network segment at CINECA have IP addresses of the INFN Tier 1 network and are used as they were installed
at the Tier 1 facility (see Figure~\ref{cineca-schema}). The data access bandwidth is 400 Gbps but it can scale up to 1,2 Tbps.
This DCI interconnection has been implemented rapidly and as a proof of concept (this is the first time this technology has been used in Italy), now it is in production and as it is becoming a stable and relevant asset for CNAF (fig.~\ref{cineca-traffic}), it is in our plan to have a second optical fiber (between CNAF and CINECA) for resiliency reasons.
This DCI interconnection has been implemented rapidly and as a proof of concept
(this is the first time this technology has been used in Italy). Currently, it is in production, and as it is becoming
a stable and relevant asset for CNAF (Figure~\ref{cineca-traffic}), we plan to have a second optical fiber between CNAF and CINECA for resiliency reasons.
\begin{figure}[h]
\begin{center}
\includegraphics[width=30pc]{cineca-schema.png}\hspace{2pc}%
\caption{\label{cineca-schema}INFN Tier-1 – CINECA Data Center Interconnection.}
\caption{\label{cineca-schema}INFN Tier 1–CINECA Data Center Interconnection.}
\end{center}
\end{figure}
......@@ -94,31 +107,39 @@ This DCI interconnection has been implemented rapidly and as a proof of concept
\begin{figure}[h]
\begin{center}
\includegraphics[width=30pc]{cineca.png}\hspace{2pc}%
\caption{\label{cineca-traffic}INFN Tier-1 – CINECA link usage}
\caption{\label{cineca-traffic}INFN Tier 1–CINECA link usage}
\end{center}
\end{figure}
\section{Security}
The network security policies are mainly implemented as hardware based ACLs on the access router and on the core switches (with a dedicated ASICS on the devices).
The network security policies are mainly implemented as hardware-based ACLs on the access router
and on the core switches (with a dedicated ASICS on the devices).
The network group, in coordination with GARR-CERT and EGI-CSIRT, also takes care of security incidents at CNAF (both for compromised systems or credential and known vulnerability of software and grid middleware) cooperating with the involved parties.
The network group, in coordination with GARR-CERT and EGI-CSIRT, takes also care of security incidents at CNAF
(both for compromised systems or credential and known vulnerability of software and grid middleware) cooperating with the involved parties.
During 2018, CNAF Security Group has been reorganized with the formal involvement of at least one representative for each unit in order to obtain a stronger coordination on security policies implementation and a faster reaction to security incidents.
During 2018, CNAF Security Group has been reorganized with the formal involvement of at least one representative
for each unit in order to obtain a stronger coordination on security policies implementation and a faster reaction to security incidents.
As always in 2018 CNAF's has had an important commitment to security which had seen it active on several fronts.
As always, in 2018 CNAF has had an important commitment to security, and it has been active on several fronts, as described in the following.
\subsection{“Misure Minime” Implementation}
CNAF has had an important role in determining how the whole of INFN would implement compliance with the “Misure Minime”\footnote{Misure Minime is a set of minimum ICT security measures to be adopted by all the Italian public administrations.} regulation. It actively contributed to the discussion and to the implementation guidelines for each OS, and had a central role in defining the Risk Management procedures, writing the prototype version and co-writing the final definition.
CNAF has had an important role in determining how the whole INFN would implement compliance with the
“Misure Minime”\footnote{Misure Minime is a set of minimum ICT security measures to be adopted
by all the Italian public administrations.} regulation.
It actively contributed to the discussion and to the implementation guidelines for each OS,
and it had a central role in defining the Risk Management procedures, writing the prototype version and co-writing the final definition.
\subsection{Vulnerability scanning}
In an effort to monitor the security of the centre, CNAF has started a campaign of systematic and periodic scanning all of its machines, personal and not, looking for vulnerabilities in an effort to find and fixing them before they could be actively exploited by an attacker.
In an effort to monitor the security of the center, CNAF has started a campaign of systematic and periodic scanning all of its machines,
personal and not, looking for vulnerabilities in an effort to find and fix them before they could be actively exploited by an attacker.
As expected, this scanning brought to light a number of issues that were promptly corrected (when possible) or mitigated (when not) thus nipping a number of potential problems in the bud.
......@@ -130,7 +151,10 @@ Focused on testing the actual security of the product and finding ways in which
\subsection{Technology tracking}
A constant technology tracking activity is ongoing on security tools and devices. In particular meeting with some the main Next Generation Firewall producers have been scheduled in 2017 and in 2018. During this two years three Next-Generation firewall from Fortinet, Huawei and Palo Alto Networks had been tested on production links in order to define the fundamental characteristics to be included in the tender for the acquisition of the NG Firewall to be installed on the “General IP” Wide Area Network Link.
A constant technology tracking activity on security tools and devices is ongoing.
In particular, meetings with some of the main Next Generation Firewall producers have been scheduled in 2017 and in 2018.
During the two years, three Next-Generation firewall from Fortinet, Huawei and Palo Alto Networks had been tested on production links
in order to define the fundamental characteristics to be included in the tender for the acquisition of the NG Firewall to be installed on the “General IP” Wide Area Network Link.
......
contributions/newchim/repnewchim18.tex
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......@@ -12,12 +12,12 @@
M.~Papa$^1$, S.~Pirrone$^{1}$, G.~Politi$^{2,1}$, F.~Rizzo$^{2,3}$,
P.~Russotto$^{3}$, A.~Trifir\`o$^{5,1}$, M~Trimarchi$^{5,1}$ }
\address{$^1$ INFN, Sezione di Catania, Italy}
\address{$^2$ Dip. di Fisica e Astronomia, Universit\`a di Catania, Italy}
\address{$^3$ INFN, Laboratori Nazionali del Sud, Catania, Italy}
\address{$^4$ CSFNSM, Catania, Italy}
\address{$^5$ Dipartimento di Scienze MITF, Universit\`a di Messina, Italy}
\address{$^6$ Universit\`a di Enna, ``Kore'', Italy}
\address{$^1$ INFN Sezione di Catania, Catania, IT}
\address{$^2$ Universit\`a di Catania, Catania, IT}
\address{$^3$ INFN Laboratori Nazionali del Sud, Catania, IT}
\address{$^4$ CSFNSM, Catania, IT}
\address{$^5$ Universit\`a di Messina, Messina, IT}
\address{$^6$ Universit\`a di Enna, Enna, IT}
\ead{defilippo@ct.infn.it}
......@@ -29,10 +29,10 @@ the 2018 experiment campaigns.
\section{Introduction}
The CHIMERA 4$\pi$ detector is constituted by 1192 Si-CsI(Tl) telescopes. The first stage of
the telescope is a 300 $\mu$m thick silicon detector followed by a CsI(Tl) crystal, having a
thickness from 6 to 12 cm in length with photodiode readout. One of the key point of this device is the low threshold for simultaneous mass and charge identifications of particles and light ions, the velocity measurement by Time-of-Flight technique and the Pulse Shape Detection (PSD) aiming to measure the rise time of signals for charged particles stopping in the first Silicon detector layer of the telescopes. The CHIMERA array was designed to study the processes responsible for particle productions in nuclear fragmentation, the reaction dynamics and the isospin degree of freedom. Studies of Nuclear Equation of State (EOS) in asymmetric nuclear matter have been performed both at lower densities with respect to nuclear saturation density, in the Fermi energy
thickness from 6 to 12 cm in length with photodiode readout. One of the key points of this device is the low threshold for simultaneous mass and charge identifications of particles and light ions, the velocity measurement by Time-of-Flight technique and the Pulse Shape Detection (PSD) aiming to measure the rise time of signals for charged particles stopping in the first Silicon detector layer of the telescopes. The CHIMERA array was designed to study the processes responsible for particle productions in nuclear fragmentation, the reaction dynamics and the isospin degree of freedom. Studies of Nuclear Equation of State (EOS) in asymmetric nuclear matter have been performed both at lower densities with respect to nuclear saturation density, in the Fermi energy
regime at LNS Catania facilities \cite{def14}, and at high densities in the relativistic heavy ions beams energy domain at GSI \cite{rus16}. The production of Radioactive Ion Beams (RIB) at LNS in the recent years has also opened the use of the 4$\pi$ detector CHIMERA to nuclear structure and clustering studies \cite{acqu16, mar18}.
FARCOS (Femtoscope ARray for COrrelations and Spectroscopy) is an ancillary and compact multi-detector with high angular granularity and energy resolution for the detection of light charged particles (LCP) and Intermediate Mass Fragments (IMF) \cite{epag16}. It has been designed as an array for particle-particle correlation measurements in order to characterize the time scale and shape of emission sources in the dynamical evolution of heavy ion collisions. The FARCOS array is constituted, in the final project, by 20 independent telescopes. Each telescope is composed by three detection stages: the first $\Delta E$ is a 300 $\mu$m thick DSSSD silicon strip detector with 32x32 strips; the second is a DSSSD, 1500 $\mu$m thick with 32x32 strips; the final stage is constituted by 4 CsI(Tl) scintillators, each one of 6 cm in length.
FARCOS (Femtoscope ARray for COrrelations and Spectroscopy) is an ancillary and compact multi-detector with high angular granularity and energy resolution for the detection of light charged particles (LCP) and Intermediate Mass Fragments (IMF) \cite{epag16}. It has been designed as an array for particle-particle correlation measurements in order to characterize the time scale and shape of emission sources in the dynamical evolution of heavy ion collisions. The FARCOS array is constituted, in the final project, by 20 independent telescopes. Each telescope is composed by three detection stages: the first $\Delta E$ is a 300 $\mu$m thick DSSSD (Double-Sided Silicon Strip Detector) with 32x32 strips; the second is a DSSSD, 1500 $\mu$m thick with 32x32 strips; the final stage is constituted by 4 CsI(Tl) scintillators, each one of 6 cm in length.
\begin{figure}[t]
\begin{center}
......@@ -49,7 +49,7 @@ The total number of GET channels for the CHIMERA + FARCOS (20 telescopes) device
\section{CNAF support for Newchim}
In the new digital data acquisition we store the sampled signals, thus producing a huge set of raw data. The data rate can be evaluated at 3-5 TB/day in a experiment (without FARCOS). For example the last CHIMERA experiment in 2018 collected a total of 70 TB of data in two weeks of beam time.
Clearly this easily saturates our local disk servers storage capabilities. We use the CNAF as main backup storage center: after data merging and processing, the raw data (signals) are reduced to physical variables in ROOT format, while the original raw data are copied and stored at CNAF. Copy is done in the {\it /storage/gpfs...} storage area in the general purpose tier1-UI machines by using the Tier-1 infrastructure and middleware software. In the future could be interesting to use also the CPU resources at CNAF in order to run the data merger and signal processing software directly on the copied data. Indeed we expect a significative increase of the storage resources needed when the FARCOS array will be fully operational.
Clearly this easily saturates our local disk servers storage capabilities. We use the CNAF as main backup storage center: after data merging and processing, the raw data (signals) are reduced to physical variables in ROOT format, while the original raw data are copied and stored at CNAF. Copy is done in the {\it /storage/gpfs...} storage area in the general purpose tier 1-UI machines by using the Tier 1 infrastructure and middleware software. In the future could be interesting to use also the CPU resources at CNAF in order to run the data merger and signal processing software directly on the copied data. Indeed we expect a significative increase of the storage resources needed when the FARCOS array will be fully operational.
\section*{References}
......@@ -64,4 +64,4 @@ Clearly this easily saturates our local disk servers storage capabilities. We us
012003
\bibitem{cas18} A. Castoldi, C. Guazzoni, T. Parsani, 2018 {\it Nuovo Cimento C} {\bf 41} 168
\end{thebibliography}
\end{document}
\ No newline at end of file
\end{document}
contributions/padme/2019_PADMEcontribution.pdf
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@misc{opennext,
url = "http://www.t3lab.it/en/progetti/open-next/"
}
@misc{harmony,
url = "https://www.harmony-alliance.eu/"
}
@misc{htn,
url = "https://www.retealtatecnologia.it/en"
}
@misc{industry40,
url = "http://www.sviluppoeconomico.gov.it/images/stories/documenti/PIANO-NAZIONALE-INDUSTRIA-40_ITA.pdf "
}
@misc{opusfacere,
url = "http://www.opusfacere.it/"
}
@article{eee,
author={M Abbrescia and S Aiola and R Antolini and C Avanzini and R Baldini Ferroli and G Bencivenni and E Bossini and E Bressan and A
Chiavassa and C Cicalo and L Cifarelli and E Coccia and D De Gruttula and S De Pasquale and A Di Giovanni and M D'Incecco and K
Doroud and M Dreucci and F L Fabbri and V Frolov and M Garbini and G Gemme and I Gnesi and C Gustavino and D Hatzifotiadu and P La
Rocca and S Li and F Librizzi and A Maggiora and M Massai and S Miozzi and R Moro and M Panareo and R Paoletti and L Perasso and F Pilo and G
Piragino and A Regano and F Riggi and G C Righini and F Romano and G Sartorelli and E Scapparone and A Scribano and M Selvi and S
Serci and E Siddi and G Spandre and S Squarcia and M Taiuti and F Toselli and L Votano and M C S Williams and A Zichichi and R Zouyevski},
title={The EEE Project: cosmic rays, multigap resistive plate chambers and high school students},
journal={Journal of Instrumentation},
volume={7},
number={11},
pages={P11011},
url={http://stacks.iop.org/1748-0221/7/i=11/a=P11011},
year={2012},
abstract={The Extreme Energy Events Project has been designed to join the scientific interest of a cosmic rays physics experiment with the enormous didactic potentiality deriving from letting it be carried out by high school students and teachers. After the initial phase, the experiment is starting to take data continuously, and the first interesting physics results have been obtained, demonstrating the validity of the idea of running a real physics investigation in these peculiar conditions. Here an overview of its structure and status is presented, together with some studies about detector performance and first physics results.}
}
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\documentclass[a4paper]{jpconf}
\usepackage{url}
%\usepackage[]{color}
\usepackage{makecell}
%usepackage{booktabs}
\usepackage{siunitx}
%\usepackage{subfig}
\usepackage{float}
%\usepackage{graphicx}
\begin{document}
\title{External Projects and Technology Transfer}
\author{C. Vistoli$^1$, B. Martelli$^1$}
\address{$^1$ INFN-CNAF, Bologna, IT}
\ead{barbara.martelli@cnaf.infn.it}
\begin{abstract}
External Projects and Technology Transfer Unit (PETT) main mission is the coordination of CNAF activities funded by external organizations (Region, Italian Ministry of Education, EU) and CNAF Technology Transfer actions. PETT Unit coordinates the INFN Technology Transfer Laboratory in Emilia Romagna (TTLab), accredited to the Emilia Romagna High Technology Network (HTN) since 2015.
In 2018 TTLab submitted 4 proposals to the POR-FESR Emilia Romagna call, and at the beginning of 2019 three of them were approved and funded: FORTRESS, WE-LIGHT and SmartChain.
In the meantime, the TROPIC project, approved in the former POR-FESR call, continued to run smoothly and the Harmony project started to move from a Proof of Concept phase to the production one.
In its first year of life, the ISO 27001 Information Security Management System (ISMS) had to manage the critical situation originated by the datacenter flood happened at the end of 2017 and it did it successfully, passing the ISO 27001 external audit without any non-conformity.
\end{abstract}
\section{Introduction}
During 2018 the External Projects and Technology Transfer (PETT) Organizational Unit has
contributed to various projects in the field of computing, communication of science, technology
transfer and education. Some of the most relevant ones are: FiloBlu (POR-FESR Regione
Marche), Opus Facere (MIUR) \cite{opusfacere}, Emilia Romagna Plan for high
competencies in Research Technology Transfer and Entrepreneurship \cite{altecompetenze}, OPEN-NEXT and TROPIC(POR-FESR
2014-2020), Harmony \cite{harmony}. Great effort has been dedicated to the
consolidation of the Technology Transfer Laboratory (INFN-TTLab) \cite{ttlab} which puts together heterogeneous
competencies (physics, computing, mechanics and electronics) from Emilia Romagna INFN
Sections and Centers (Bologna, Ferrara and CNAF) in order to promote the transfer of INFN
know-how toward regional enterprises. In 2018 we operated the first year of life of the ISO-27001 ISMS consisting of a subset of INFN Tier 1 resources. This was required in order
to store and manage private and sensitive personal data and could open new opportunities of
exploitation of the Tier 1 resources in the near future.
\section{The TROPIC project}
TTLab is coordinating the TROPIC project (Target for Radioisotope Production via anti-Channelling) \cite{tropic} in a consortium with COMECER and Biomeccanica Srl.
The project is part of the European Regional Development Plan POR-FESR Axis 1, Research and Innovation 2014-2020 of the Emilia-Romagna region. Axis 1 aims at strengthening the regional network of research and technology transfer to companies with the purpose of increasing the ability to bring innovative solutions and products to the market. Through collaborations with researchers, it promotes innovation paths in the strategic areas of the regional production system and strengthens the high-tech network.
The TROPIC project intends to explore a new radioisotope production method through the irradiation of solid targets in which a quantum effect called anti-channelling is exploited. Thanks to this effect, the probability of impact of the particle emitted by the accelerator on a crystalline matrix is much higher than the same dynamic but with a traditional amorphous solid target. This leads to an increase in the yield of nuclear bombardment and thus produces the desired isotope in larger quantities. The project intends to evaluate how much it is possible to save in terms of cost of the enriched material and how much the reaction yield grows in this particular configuration of the target. The ultimate goal is to make the production of these isotopes, extremely interesting from a diagnostic and therapeutic point of view, easier and less expensive.
The theoretical research activity has already produced various results published in the past years. The next step will be the experimental test and the realization of the first prototype.
\section{The HARMONY Alliance}
The HARMONY project (Healthcare alliance for resourceful medicines offensive against neoplasms in hematology) \cite{harmony} is part of IMI2 Big Data for Better Outcomes programme, which aims to facilitate the use of diverse data sources to deliver results that reflect health outcomes of treatments that are meaningful for patients, clinicians, regulators, researchers, healthcare decision-makers, and others.
Blood cancers, or haematologic cancers (e.g. leukaemia, lymphoma and myeloma), affect the production and function of blood cells and account for about one third of cancer cases in children and about one third of cancer deaths. As many blood cancers are rare, and healthcare practice varies across EU, a lack of data on relevant outcomes represents a challenge for clinicians, researchers, and decision-makers alike. The HARMONY project aims to use big data to deliver information that will help to improve the care of patients with these diseases. Specifically, the project will gather together, integrate and analyze anonymous patient data from a number of high quality sources. This will help the team to define clinical endpoints and outcomes for these diseases that are recognized by all key stakeholders. Meanwhile the project data sharing platform will facilitate and improve decision making for policy makers and clinicians alike to help them to give the right treatment to the right patient at the right time. More broadly, the project will result in a pan-European network of stakeholders with expertise in this disease area.
TTLab is involved as Linked Third Party of University of Bologna and is in charge of providing and managing the Harmony Big Data Platform Hosting in compliance with the ISO/IEC-27001 certification.
\section{Other regional and national activities}
In 2018, as industrial research lab of the Emilia Romagna High Technology Network \cite{htn}, TTLab carried out a number of activities in order to strengthen the link between research and industry sector.
In 2018 TTLab kept on contributing in the following Emilia Romagna Clust-ERs \cite{clusters}:
\begin{itemize}
\item[--]INNOVATE (ICT): focused on the role of digital technologies as a means for innovate services in a global context and to emphasize their transformative power of the economy and society.
\item[--]AGRIFOOD: covers the whole “from farm to fork” value chain, starting from the farmed produce all the way to the consumers’ plates, it includes ICT systems, equipment and machineries, transformation and packaging plants, logistics and food by-products and waste valorization.
\item[--]CREATE: aims to improve the innovation in the culture and creative industries sector
\item[--]HEALTH: focused on health related topics like biomed, pharmaceutical and omics sciences, smart and active living. In Emilia-Romagna there is the most important medtech district in Europe and regional policies encourage local research actors to team-up with private companies in order to maximize innovation.
\item[--]MECH: focused on the mech
nics and motor sector. A number of worldwide famous brands both in the automotive and in the mechanical sector are located in the region. These companies are at the cutting edge of a corporate system and can take advantage of technologies developed by our research teams.
\item[--] BUILD: supports the innovation system in the building and construction field.
\end{itemize}
Clust-ERs are recognized Associations, formed in accordance with articles 14-42 of the Italian Civil Code. Clust-ER Associations are communities of public and private bodies (research centers, businesses, training bodies) that share ideas, skills, tools, and resources to support the competitiveness of the most important production systems in Emilia-Romagna. Thanks to Clust-ERs, research laboratories and centers for innovation belonging to the High Technology Network team up with the business system and the higher education system to make up the inter-disciplinary critical mass necessary to multiply opportunities and develop strategic projects with a high regional impact. Main objectives of Clust-ERs are: to maximize the opportunities for participating in European programs and international research and innovation networks, to forge synergies and set up coordinated and stable networks and connections with other public/private agglomerations operating in the same sectors at national and European level, to encourage and support the development and creation of initiatives in higher education and the development of human resources and to support the development of new research infrastructures.
INFN is part of the National Cluster ``Intelligent Factories'' \cite{cfi}: an association that includes large and medium-small companies, universities and research centers, company associations and other stakeholders active in the advanced manufacturing sector. The association is recognized by MIUR as a driver of sustainable economic growth in all the regions of the national economic system, as it fosters the innovation and specialization of Italian manufacturing systems. The mission of CFI is to increase the competitiveness of the Italian manufacturing industry through the design and implementation of a number of research projects for the development of new enabling technologies; to maintain and develop advanced skill in Italian manufacturing; to increase Italian companies access to national and international funds; to support entrepreneurship and company growth through the involvement of private investors. The INFN participates in this National Cluster through INFN personnel.
TTLab participates in the Opus Facere project (Lab for Employability) \cite{opusfacere} with a course about Cosmic Rays Data Analysis, on the EEE \cite{eee} experiment data, where students of the fifth year of secondary school can understand and practice the job of data scientist and physicist. For more details, see dedicated contribution in this report.
In 2018 TTLab started the activities founded by the Regional Plan for High Competencies for Research, Technology Transfer and Entrepreneurship \cite{altecompetenze} (5 research grants) for industrial research activities in different areas: models and algorithms for genome sequencing analysis, geospatial data access and processing services, big data analysis of physical, astrophysical and aerospatial data, big data analysis for smart cities. In particular, the research grants activated are:
\begin{itemize}
\item[--]Big Data Analysis: algorithms and models for the analysis of nucleic acid sequencing data - partner CIG/Unibo
\item[--]Big Data management: services for accessing and processing geospatial data in the era of Big Data – Industrial partner MEEO s.r.l \cite{meeo} Meteorological Enviromental Earth Observation
\item[--]Big Data management: the analysis of data in the field of physics, astrophysics and space science industrial partner VEM Sistemi S.p.A \cite{vem}
\item[--]Big Data management: Big Data in Smart Cities Industrial partner Filippetti S.p.A \cite{filippetti}
\end{itemize}
Three out of four proposals to Emilia Romagna POR-FESR 2018 call were funded:
\begin{itemize}
\item[--] FORTRESS: coordinated by INFN-TTLab, targets the innovative use of thin film transistors as direct radiation detectors integrated into large area flexible patches for two innovative applications. Two demos will be developed: SAFEINJECT and BEAMGUARD.
Two advanced material platforms: organic and perovskite thin films. They share the unique capability of realizing simple, thin and flexible transistors able to directly detect ionizing radiation and apt to be fabricated as thin, lightweight, low-power operated, large-area 2D pixelated matrices.
\item[--] WE-LIGHT (WEarable LIGHTing for smart accessories and apparels): coordinated by UniMoRe with participation of INFN-TTLab, proposes the creation of prototypes of sportswear integrated with different technological systems of electronic, optical and sensorial type, able to connect whoever wear to the external environment.
\item[--] SmartChain: coordinated by UniMoRe with participation of INFN-TTLab, proposes the creation of a set of solutions based on
blockchain technologies to identify and implement innovative platforms useful to businesses of the Emilia Romagna territory. The project will analyze the current production, certification and tracking scenarios supply chains, proposing and implementing software systems that can improve the efficiency of production chains.
\end{itemize}
Finally, PETT coordinated the participation of INFN to the BI-REX (Big data Innovation and Research Excellence) Competence Center and actively contributed to the proposal. The BI-REX Competence Center is a project funded by the Ministry of Economic Development in the scope of Industry-4.0 plan. It is composed by a pilot plant which aims to reconstruct an entire digital manufacturing process for mechanical components, which can demonstrate the potential of new technologies for production, while allowing the realization of finished products that can be used directly as demonstrators for different supply chains such as the automotive, mechatronics and biomedical industries.
The pilot will be assisted by ICT systems for dynamic monitoring and reconfiguration of the various islands,
both separately and in integration, and elastic cloud / edge platforms for data collection and analytics from
sensors.
The Bi-Rex Competence Center involves 49 companies, 7 universities and 5 research institutions and it is cofounded by Ministry of Economic Development and private partners. The total amount of the founding is about 20 MEuro.
Bi-Rex main area of research are:
\begin{itemize}
\item[--] Additive Manufacturing
\item[--] ICT and automation in manufacturing industries
\item[--] Big Data and new digital business models
\item[--] Logistics
\item[--] Environmental and economical sustainability
\end{itemize}
CNAF will contribute to the Competence Center with its expertise on Big Data management and on Cloud integration with HPC, IoT and Edge technologies.
\section{SUPER}
INFN-TTLab worked on the proposal preparation and participates in the SUPER Supercomputing infrastructure and Big Data Analytics for advanced applications in the field of life sciences, advanced materials and innovative production systems. The partnership is composed of 12 subjects and includes the major regional players for the following areas:
\begin{itemize}
\item[--] Supercomputing and big data: CINECA, INFN, which have world-class infrastructures, CMCC, and
ENEA, which have national Tier 1 class systems; CNR, INAF and INGV that have departmental systems
and qualifying databases within their institutional contexts.
\item[--] Genomics, regenerative medicine, and biobanks: University of Bologna, University of Modena and
Reggio Emilia, Rizzoli Orthopedic Institutes, University of Ferrara and University of Parma.
\item[--] Innovative industrial materials and systems: University of Bologna, University of Modena and Reggio
Emilia, CNR, University of Ferrara, University of Parma, ENEA.
\end{itemize}
\section{Outreach}
INFN CNAF Knowledge Transfer strategy roots in its connections with the INFN central structures related to this purpose (INFN External funds unit and INFN National Technology Transfer Committee) and takes advantage of its relationships with local economy and regional administration. The PETT Unit is coordinating the actions needed to translate this strategy into reality. CNAF and the PETT Unit are strongly committed to leverage the virtuous relationship between the datacenter personnel's big-data competencies and the R\&D activities, both at the forefront of technology, in order to bring back to society this innovation force. In fact, thanks to the experience gained running the LHC computing infrastructures, CNAF personnel is probably within the most skilled staffs in Italy in the field of big data management and HPC computing. Moreover, in the field of Cloud Computing CNAF has a primary role as R\&D actor and integrator of Cloud technologies with Internet of Things, Low Power computing and Edge computing systems.
All of them (big data, HPC and cloud computing) are some of the key technologies mentioned by the Italian Ministry of Economic Development National Plan Impresa 4.0 (formerly Industria 4.0) as a driver to improve competitiveness in the industrial sector, making CNAF one of the most promising actors in the technology transfer field.
INFN mission includes, in addition to research, the transfer to the society of the acquired knowledge. This definition means both the transfer of know-how in the form of training and technology transfer, and the dissemination of scientific culture. In order to make its intervention more effective, in 2016 the INFN was equipped with a Coordination Committee for the Third Mission (CC3M). The primary objective of this Committee is to coordinate local initiatives for the dissemination of scientific culture with national impact to strengthen its effectiveness. CNAF is linked to CC3M through a local representative (from the PETT Unit) whom reports local activities to the Committee.
Main outreach activities performed by CNAF personnel are:
\begin{itemize}
\item[--] Training internships (summer students, curricular internships) \cite{summerstudents}
\item[--] Guided tours in the Tier 1 datacenter premises
\item[--] Coordination and holding of University and PhD courses on the topic of Infrastructure for Big
Data processing
\item[--] Outreach events like The European Researchers' Night 2017 an initiative promoted by the European Commission since 2005 (Marie Sklodowska-Curie actions) which involves thousands of researchers and research institutions in all European countries every year. It takes place every year throughout Europe on the last Friday of September. The goal is to create opportunities for researchers and citizens to meet to spread the scientific culture and knowledge of research professions in an informal and stimulating context. CNAF contributes to events such as live scientific experiments and demonstrations, exhibitions and guided tours, conferences and informative seminars, shows, concerts and artistic performances.
\item[--] School-work alternation within the OpusFacere Territorial Laboratory for Employability \cite{opusfacere}an innovative educational project that comes from a network composed by educational institutes of the Metropolitan City of Bologna and public and private partners of the territory. In this context,
CNAF designed and hold a course named Cosmic Rays Data Analysis based on data collected by the Extreme Energy Events project and aimed at teach high school students the job of physicist \cite{eee-opusfacere}.
\end{itemize}
\section{Conclusions}
In 2018 the External Projects and Technology Transfer group consolidated its collaboration with the research and innovation regional system participating and contributing to many initiatives aimed at creating a strong partnership between the research and industry sectors.
\section*{References}
\begin{thebibliography}{9}
\bibitem{altecompetenze} \url{https://formazionelavoro.regione.emilia-romagna.it/alta-formazione-ricerca/approfondimenti/piano-alte-competenze}, site visited on June 2019.
\bibitem{harmony} \url{https://www.harmony-alliance.eu/},site visited on June 2019.
\bibitem{ttlab} \url{https://ttlab.infn.it/}, site visited on June 2019.
\bibitem{tropic} \url{https://agenda.infn.it/event/15101/contributions/28472/attachments/20303/23011/TROPIC_20190213_ebagli.pdf}, site visited on June 2019.
\bibitem{htn} \url{https://www.retealtatecnologia.it/en}, site visited on June 2019.
\bibitem{clusters} \url{https://www.retealtatecnologia.it/en/clust-er site}, visited on June 2019.
\bibitem{cfi} \url{https://www.fabbricaintelligente.it/}, site visited on June 2019.
\bibitem{meeo} \url{http://www.meeo.it/wp/}, site visited on June 2019.
\bibitem{vem} \url{https://vem.com/en/}, site visited on June 2019.
\bibitem{filippetti} \url{https://www.filippetti.it/en/}, site visited on June 2019.
\bibitem{opusfacere} \url{http://www.opusfacere.it/}, site visited on June 2019.
\bibitem{eee} \url{https://eee.centrofermi.it/}, site visited on June 2019.
\bibitem{eee-opusfacere} Martelli B, Noferini F, Pellegrino C, Ronchieri E, Vistoli C, Seminar \emph{Cosmic Rays Data Analysis: insegnando Python con un Jupyter Notebook} \url{https://agenda.infn.it/event/19607/}, site visited on June 2019.
\bibitem{summerstudents} \url{https://agenda.infn.it/event/17430/}, site visited on June 2019.
\end{thebibliography}
\end{document}