Improvements of the GPU Processing Framework for ALICE

ALICE is the dedicated heavy ion experiment at the LHC at CERN and records lead-lead collisions at a rate of up to 50 kHz. The detector with the highest data rate of up to 3.4 TB/s is the TPC. ALICE performs the full online TPC processing corresponding to more than 95% of the total workload on GPUs, and when there is no beam in the LHC, the online computing farm’s GPUs are used to speed up the offline processing. After the deployment of the first version of the online TPC processing needed for data taking, ALICE has implemented many improvements to its GPU processing framework. These include a run time compilation mode applying on the fly optimizations, improvements to parallelize / speed up the GPU compilation, debugging modes to guarantee reproducible and deterministic results in concurrent reconstruction, and framework features to leverage common components in the code of different detectors. The talk will give an overview of the ALICE experience with GPUs in online and offline processing and present the latest GPU processing framework features.

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Publication Details

Journal
EPJ Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/epjconf/202533701362
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
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article

Improvements of the GPU Processing Framework for ALICE

D. Røhr
EPJ Web of Conferences
Advanced Data Storage Technologies
article

Improvements of the GPU Processing Framework for ALICE

D. Røhr
article en

Abstract

ALICE is the dedicated heavy ion experiment at the LHC at CERN and records lead-lead collisions at a rate of up to 50 kHz. The detector with the highest data rate of up to 3.4 TB/s is the TPC. ALICE performs the full online TPC processing corresponding to more than 95% of the total workload on GPUs, and when there is no beam in the LHC, the online computing farm’s GPUs are used to speed up the offline processing. After the deployment of the first version of the online TPC processing needed for data taking, ALICE has implemented many improvements to its GPU processing framework. These include a run time compilation mode applying on the fly optimizations, improvements to parallelize / speed up the GPU compilation, debugging modes to guarantee reproducible and deterministic results in concurrent reconstruction, and framework features to leverage common components in the code of different detectors. The talk will give an overview of the ALICE experience with GPUs in online and offline processing and present the latest GPU processing framework features.

EPJ Web of ConferencesVol. 337
European Organization for Nuclear Research (CH)
Openalex Percentile: Top 67%
Advanced Data Storage Technologies
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Improvements of the GPU Processing Framework for ALICE — D. Røhr · EPJ Web of Conferences (2025) | TGRS Research Map | TGRS