Alice Weekly Meeting: Software for Hardware Accelerators / PDP-SRC - MINUTES ONLY

Wednesday 11 Dec 2024, 10:00 → 11:30 Europe/Zurich

10:00 → 10:20 Discussion

Speakers: David Rohr (CERN), Giulio Eulisse (CERN)

10:20 → 10:25 Following up JIRA tickets

Speaker: Ernst Hellbar (CERN)

Low-priority framework issues https://its.cern.ch/jira/browse/O2-5226

• Grafana metrics: Might want to introduce additional rate metrics that subtract the header overhead to have the pure payload: low priority.

• Merged workflow fails if outputs defined after being used as input
  • needs to be implemented by Giulio
• Cannot override options for individual processors in a workflow
  • requires development by Giulio first 
• Problem with 2 devices of the same name
• Usage of valgrind in external terminal: The testcase is currently causing a segfault, which is an unrelated problem and must be fixed first. Reproduced and investigated by Giulio.
• Run getting stuck when too many TFs are in flight.
• Do not use string comparisons to derrive processor type, since DeviceSpec.name is user-defined.
• Support in DPL GUI to send individual START and STOP commands.
• Add additional check on DPL level, to make sure firstOrbit received from all detectors is identical, when creating the TimeFrame first orbit.
• Implement a proper solution to detect wheter a device is firstInChain 
• Deploy topology with DPL driver

 

PDP-SRC issues

• Check if we can remove dependencies on /home/epn/odc/files in DPL workflows to remove the dependency on the NFS
  • reading / writing already disabled
  • remaining checks for file existence?
  • check after Pb-Pb by removing files and find remaining dependencies
• logWatcher.sh and logFetcher scripts modified by EPN to remove dependencies on epnlog user
  • node access privileges fully determined by e-groups
  • new log_access role to allow access in logWatcher mode to retrieve log files, e.g. for on-call shifters
  • to be validated on STG
  • waiting for EPN for further feedback and modifications of the test setup
• computing estimate for 2024 Pb-Pb
  • originally assumed 305 EPNs suffucient, but needed 340 EPNs (5 % margin) in the end
    • 11 % difference 
    • estimate from 2023 Pb-Pb replay data with 2024 software
  • average hadronic interaction rate of Pb-Pb replay timeframes with pile-up correction for ZDC rate
    • formula: IR_had = -ln(1 - rate_ZDC / (11245*nbc) ) * 11245 * nbc * 7.67 / 214.5
    • 2023, 544490, nbc=1088, rate_ZNC=1166153.4 Hz: IR_had = 43822.164 Hz
    • 2024, 560161,  nbc=1032, rate_ZNC=1278045.2 Hz: IR_had = 48417.767 Hz
    • 10.5 % difference in IR from 2023 relpay to 2024 replay
    • 7 % to 47 kHz assumed for the 2023 replay data (?) when estimating the required resources
      • • could at least explain part of the difference between the estimated and observed margins
• environment creation
  • cached topologies
    • in practice, only works when selecting only one detector or when defining the Detector list (Global)  specifically in the EPN ECS panel
      • when using default, the list of detectors is taken from default variables in ECS
        • not yet clear where this is set, it obviously depends on the selected detectors
        • the order of detectors is always different, even for identical environments, therefore, the topology hash is also different and the cached topologies are not used
        • investigating together with ECS team
  • start-up time
    • ~80 sec spent in state transitions from IDLE to READY 
    • will profile state transitions with export DPL_SIGNPOSTS=device  to determine if we wait for single slow tasks or if some other part (e.g. DDS) is slow

10:25 → 10:30 TPC ML Clustering

Speaker: Christian Sonnabend (CERN, Heidelberg University (DE))

10:30 → 10:35 ITS Tracking

Speaker: Matteo Concas (CERN)

 

ITS GPU tracking

• General priorities:
  • Focusing on porting all of what is possible on the device, extending the state of the art, and minimising computing on the host.
  • Optimizations via intelligent scheduling and multi-streaming can happen right after.
  • Kernel-level optimisations to be investigated.
• Move remaining track-finding tricky steps on GPU
  • ProcessNeighbours kernel has been ported and validated.
  • Now fixing the logic that concatenates its usage multiple times as it is still faulty.
• TODO:
  
  • Reproducer for HIP bug on multi-threaded track fitting: no progress yet.
  • Fix possible execution issues and known discrepancies when using gpu-reco-workflow : no progress yet; will start after the tracklet finding is ported.

DCAFitterGPU

• Deterministic approach via using SMatrixGPU on the host, under particular configuration: no progress yet.

10:35 → 10:45 TPC Track Model Decoding on GPU

Speaker: Gabriele Cimador (Universita e INFN Trieste (IT))

10:45 → 10:55 Efficient Data Structures

Speaker: Dr Oliver Gregor Rietmann (CERN)

Efficient Data Structures

In order to onboard Jolly (collaborator from ROOT) on the code more easily, I did the following:

• Added unit tests
• Added diagnostic functions (e.g. to count number of constructor calls, copies, moves, ...)
• Set up easy benchmarks (still ongoing).