Author:
Kortelainen Matti J.,Kwok Martin,Childers Taylor,Strelchenko Alexei,Wang Yunsong,
Abstract
Programming for a diverse set of compute accelerators in addition to the CPU is a challenge. Maintaining separate source code for each architecture would require lots of effort, and development of new algorithms would be daunting if it had to be repeated many times. Fortunately there are several portability technologies on the market such as Alpaka, Kokkos, and SYCL. These technologies aim to improve the developer’s productivity by making it possible to use the same source code for many different architectures. In this paper we use heterogeneous pixel reconstruction code from the CMS experiment at the CERNL LHC as a realistic use case of a GPU-targeting HEP reconstruction software, and report experience from prototyping a portable version of it using Kokkos. The development was done in a standalone program that attempts to model many of the complexities of a HEP data processing framework such as CMSSW. We also compare the achieved event processing throughput to the original CUDA code and a CPU version of it.
Reference28 articles.
1. Worpitz B., Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures (2015)
2. Zenker E., Worpitz B., Widera R., Huebl A., Juckeland G., Knüpfer A., Nagel W.E., Bussmann M., Alpaka - An Abstraction Library for Parallel Kernel Acceleration (IEEE Computer Society, 2016), 1602.08477
3. Matthes A., Widera R., Zenker E., Worpitz B., Huebl A., Bussmann M., Tuning and optimization for a variety of many-core architectures without changing a single line of implementation code using the Alpaka library (2017), 1706.10086
4. Edwards H.C., Trott C.R., Sunderland D., Journal of Parallel and Distributed Computing 74, 3202 (2014)
5. Beckingsale D.A., Burmark J., Hornung R., Jones H., Killian W., Kunen A.J., Pearce O., Robinson P., Ryujin B.S., Scogland T.R.W., RAJA: Portable Performance for LargeScale Scientific Applications (2019), IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), p. 71
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献