Session

DescriptionThanks to their dedicated architecture, graphical processing units (GPUs) are the workhorse of parallel computing and drove the majority of growth in computation power in the recent decade. The data processing pipeline in high energy physics is a very heterogeneous application, composed of dedicated algorithms, some that parallelize and others that do not. While porting algorithms to GPU programming frameworks like CUDA has its own challenge, some other algorithms need to be rethought from the ground up so as to take advantage of the tremendous throughput of modern devices. We propose a review of large scale use of GPUs in high energy physics data processing, including event reconstruction, simulation, triggering and analysis. We wish to demonstrate the challenges in adopting this technology and discuss the way forward within the community. With this, we hope to provide a good overall picture of the current advancements and challenges in using GPUs in production.