GPUs for real-time processing in HEP trigger systems

15th International Workshop on Advanced Computing and Analysis Techniques in Physics Research

物理学;计算机科学

Paolucci, Ps^1 ; Collaboration, Gap^1 ; Ammendola, R.^1 ; Biagioni, A.^1 ; Deri, L.^2 ; Fiorini, M.^3 ; Frezza, O.^1 ; Lamanna, G.^4 ; Cicero, F Lo^1 ; Lonardo, A.^1 ; Messina, A.^1,5,6 ; Sozzi, M.^2,4 ; Pantaleo, F.^2,4 ; Paolucci, P.^1 ; Rossetti, D.^1 ; Simula, F.^1 ; Tosoratto, L.^1 ; Vicini, P.^1

INFN Roma, P.le A.Moro 2, 00185 Rome, Italy^1

Pisa University, Largo B.Pontecorvo 3, 56127 Pisa, Italy^2

Ferrara University, Via Saragat 1, 44122 Ferrara, Italy^3

INFN Pisa, laro B.Pontecorvo 3, 56127 Pisa, Italy^4

Roma University, P.le A.Moro 2, 00185 Rome, Italy^5

CERN, Geneve, Switzerland^6

关键词: General-purpose computing;    High energy physics experiments;    Innovative approaches;    Off-line computation;    Parallel com- puting;    Particle physics experiments;    Real-time application;    Realtime processing;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/523/1/012007/pdf
DOI  :  10.1088/1742-6596/523/1/012007

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

We describe a pilot project (GAP-GPU Application Project) for the use of GPUs (Graphics processing units) for online triggering applications in High Energy Physics experiments. Two major trends can be identified in the development of trigger and DAQ systems for particle physics experiments: the massive use of general-purpose commodity systems such as commercial multicore PC farms for data acquisition, and the reduction of trigger levels implemented in hardware, towards a fully software data selection system ("trigger- less"). The innovative approach presented here aims at exploiting the parallel computing power of commercial GPUs to perform fast computations in software not only in high level trigger levels but also in early trigger stages. General-purpose computing on GPUs is emerging as a new paradigm in several fields of science, although so far applications have been tailored to the specific strengths of such devices as accelerators in offline computation. With the steady reduction of GPU latencies, and the increase in link and memory throughputs, the use of such devices for real-time applications in high energy physics data acquisition and trigger systems is becoming relevant. We discuss in detail the use of online parallel computing on GPUs for synchronous low-level triggers with fixed latency. In particular we show preliminary results on a first test in the CERN NA62 experiment. The use of GPUs in high level triggers is also considered, the CERN ATLAS experiment being taken as a case study of possible applications.