Performance Study Of Gpus In Real-Time Trigger Applications For Hep Experiments
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON TECHNOLOGY AND INSTRUMENTATION IN PARTICLE PHYSICS (TIPP 2011)(2012)
Abstract
Graphical Processing Units (GPUs) have evolved into highly parallel, multi-threaded, multicore powerful processors with high memory bandwidth. GPUs are used in a variety of intensive computing applications. The combination of highly parallel architecture and high memory bandwidth makes GPUs a potentially promising technology for effective real-time processing for High Energy Physics (HEP) experiments. However, not much is known of their performance in real-time applications that require low latency, such as the trigger for HEP experiments. We describe an R&D project with the goal to study the performance of GPU technology for possible low latency applications, performing basic operations as well as some more advanced HEP lower-level trigger algorithms (such as fast tracking or jet finding). We present some preliminary results on timing measurements, comparing the performance of a CPU versus a GPU with NVIDIA's CUDA general-purpose parallel computing architecture, carried out at CDF's Level-2 trigger test stand. These studies will provide performance benchmarks for future studies to investigate the potential and limitations of GPUs for real-time applications in HEP experiments. (C) 2012 Published by Elsevier B.V. Selection and/or peer review under responsibility of the organizing committee for TIPP 11.
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Key words
HEP Trigger, GPU, CPU, Fast track-fitting, Tracking trigger
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