KHUK - DIGITALISATION PRIORITIES - ERUM-DATA COMMUNITY MEETING JAN 18/19 - ONLINE KILIAN SCHWARZ (GSI) - DESY INDICO
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Komitee für Hadronen- und Kernphysik KHuK – digitalisation priorities ErUM-Data Community meeting Jan 18/19 - Online Kilian Schwarz (GSI)
table of contents Komitee für Hadronen- und Kernphysik
motivation
KHuK digitalisation requirements
ongoing and upcoming projects
summary
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 2
ALICE online computing/CERN
Komitee für Hadronen- und Kernphysik
increased requirements for ALICE@Run3
O2 Data Rates in GB/s for Pb-Pb @ 50 kHz
• continuous untriggered stream of data, have to
be distributed from about 250 First Level
Processor nodes (FLPs) to about 1500 Event
Processing Nodes (EPNs).
• TPC clusters not belonging to tracks are
suppressed
• in the end about 90 GB/s are written to Disk
graphic from
P. Buncic
CBM online computing/FAIR Tier0 Komitee für Hadronen- und Kernphysik
CBM DAQ and online event selection novel readout system:
• free running data aqcuisition without
hardware triggers
• continous stream of time stamped
detector data
• full track and event reconstruction in real
First-level time
Event • online data reduction (>100) by a
Selector software trigger on events
• about 20 PB collected annually for offline
analysis
Hit and track time distribution for Au+Au 10A GeV collisions at 10 MHz (UrQMD) GSI Green IT Cube
high rack storage, 100,000 cores
only 5% of total energy consumption
needed for cooling
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 4
PANDA online processing/FAIR Tier0 Komitee für Hadronen- und Kernphysik
• software trigger with full event
reconstruction
• no fixed time between events time
reconstruction of event
• all data from sub-detectors with time
stamps and varying resolution.
• higher efficiency by dynamically
allocating resources
• full online event reconstruction
• event filtering by additional factor 10
• 200 GByte/s • FPGA based pre-processing • 200 MByte/s for offline analysis
input data • data reduction by factor 10
Theory – Lattice QCD Komitee für Hadronen- und Kernphysik
Software and
Data Reduction and Transformation Algorithmic Tools
published results,
open access, arXiv MB analysis-specific
collaboration codes and tools
specific data physical quantities
analysis and relation to
experimental data analysis frameworks &
GB statistical tools
lattice data analysis
workflow
Data Lake data reduction: analysis- and HW-
derived data sets, e.g. TB
optimized codes,
correlators, cumulants pre-selection of un-
correlated data sets
Lattice stored ensembles
Data Grid – big data sets -- PB
HPC hard- MC simulations to access to hardware at
ware access generate „raw“ noisy data European HPC centers
& university clusters
and many smaller communities which need to
be included Komitee für Hadronen- und Kernphysik
S-DALINAC
HADES
FAIR Phase 0 in JINR, JLAB, BNL, BES III, RIKEN and Theory
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 7
table of contents Komitee für Hadronen- und Kernphysik
motivation
KHuK digitalisation requirements
ongoing and upcoming projects
summary
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 8
online computing Komitee für Hadronen- und Kernphysik
HuK experiments do real time reconstruction and event selection on large online
farms. The following topics have therefore a high priority:
continuous read out of (all) sub detectors at very high interaction rates
real-time systems require algorithmic performance
− better and faster algorithms need to be developed enabling parallel processing
of new data structures allowing parallel data streams, joint efforts are needed
highly efficient usage of hardware resources, and low latency
online alignment and calibration
online reconstruction
− event reconstruction and selection w.r.t. signatures of rare observables in real-time
− online 4D tracking
− fast time based event building
online NN/ML/DL
− new techniques need to be applied for real time decisions based on reliable analysis
and be made available on dedicated hardware like FPGA
− required for PID, trigger channel selection, ...
data irreversibility issue online data reduction has to be done with care
same algorithms needed preferably for online and offline
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 9
Big Data Analytics Komitee für Hadronen- und Kernphysik
especially for the smaller HuK communities common simulation & analysis tools are needed
which run on new generations of high performance computers
− common code basis, also for the use of novel resources like GPUs would be helpful
new algorithms and methods need to be applied to the experiment frameworks, which
includes ML, NN, DL, MVA, bayesian tools for statistical analysis, quantum computing
− for particle identification
− for calibration/reconstruction
• e,g, for calibration of ALICE TPC space charge distortions
and fluctuations. At run 3, Pb-Pb @ 50 kHz a calibration
interval of 5 ms is required. Method via CNN and supervised
learning fast prediction.
• fast reconstruction to close the resource challenge gap
− for analysis
• of rare probes, secondary decay vertecies, rejection of large combinatorial background
employing ML and DL for efficient, fast, accurate event generation and detector simulation
including correlated and uncorrelated background via generative models.
FPGA programming (e.g. as time to digital converter with high time precision)
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 10Federated Infrastructures Komitee für Hadronen- und Kernphysik
gigantic amounts of data volume of 100s of PB/year which need to be stored, distributed and
complex information to be extracted requires new approaches
development of Data Lakes as new and more centralised storage concepts
− including intelligent Big Data Management
− efficient data access from anywhere
efficient usage and integration of new heterogenous resources as HPC centres, super computers
and Cloud systems in federated computing and storage systems (as e.g. WLCG)
− development of improved dynamic data caches
− workflow and framework optimisation
− application of virtualisation techniques in standard workflows
− usage of new architectures as GPU clusters via architecture
overarching data processing
more efficiency and flexibility through common usage of
federated resources ErUM Science Cloud
increased network bandwidth between centres
development of a federated infrastructure for FAIR
figure taken from PUNCH4NFDI
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 11Research Data Management Komitee für Hadronen- und Kernphysik
open data German infrastructure desirable for this service
open science
− everything used to obtain published results must be open
− reference guides for publishing data and sofware, partnerships with publishers
• long term software support needs to be guaranteed, repositories need to be curated
sustainability of software development and frameworks
reproducibility of analysis workflows
− application of modern analysis techniques as Jupyter NB
research data management following the FAIR
principles
− data must be Findable, Accessible, Interoperable,
Reusable
− new metadata schemes including DOIs
− standardised protocols and formats for data access
− interfaces for experiment overarching data analysis publication
also smaller HuK communities need to be included
full data life cycle needs to be supported
figure taken from DMA@MT
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 12person power considerations Komitee für Hadronen- und Kernphysik
funding is needed for hiring software and computing experts
− keeping expert person power
− long term preservation of acquired competences
education and training of users and developers in new technologies
dissertations and publications in the area of computing need to be supported
new curricula including more computing courses
interdisciplinary work with other sciences as well as industry should be encouraged
increase IT awareness in the HuK community
− e.g. introduce computing tracks in DPG (ongoing)
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 13table of contents Komitee für Hadronen- und Kernphysik
motivation
KHuK digitalisation requirements
ongoing and upcoming projects
summary
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 14selection of ongoing and upcoming projects Komitee für Hadronen- und Kernphysik
These projects are a good starting
point. But by far not everything is
covered yet. Crucial projects come to
an end. It is not clear yet if the
upcoming projects will start and
2019-22 when. The interaction between these
projects is also not always clear.
POF IV
(2021-27) new topic: DMA
ErUM-Data
2018-21 starting now Hub
start 2021? start 2022?
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 15table of contents Komitee für Hadronen- und Kernphysik
motivation
KHuK digitalisation requirements
ongoing and upcoming projects
summary
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 16summary Komitee für Hadronen- und Kernphysik
large scale Computing challenges lie ahead of the KHuK communities and need to be solved
now
a wide range of computing demands have to be satisfied: from large scale online computing
installations at the experiments to HPC systems for theory and analysis, as well as support
for the many smaller experiments and groups in the HuK community
KHuK participates in many existing and upcoming projects, which is a good start, but by far
not everything is covered and it is still unclear if all projects will be funded
KHuK computing demands stretch over all areas of Erum-Data: Big Data Analytics,
Federated Infrastructures, Research Data Management
HuK communities would benefit tremendously from increased training/education and better
career paths in computing related activities
common projects with ErUM communities and common usage of federated IT resources is
part of the strategy
Kilian Schwarz I ErUM-Data Community meeting I Online I 18-19 Jan 2021 17You can also read
