将CMS异构像素重建移植到Kokkos
Porting CMS Heterogeneous Pixel Reconstruction to Kokkos
摘要：
除了CPU之外，为各种计算加速器进行编程是一项挑战。为每个架构维护单独的源代码将需要大量的工作，并且如果必须重复多次，则新算法的开发将是令人生畏的。幸运的是，市场上有几种可移植性技术，如Alpaka、Kokkos和SYCL。这些技术的目的是提高开发人员的生产力，使其能够使用相同的源代码为许多不同的架构。在本文中，我们使用异构像素重建代码从CMS实验在CERNL LHC作为一个现实的使用情况下，GPU为目标的HEP重建软件，并报告从原型的便携式版本，它使用Kokkos的经验。开发是在一个独立的程序中完成的，该程序试图对HEP数据处理框架（如CMSSW）的许多复杂性进行建模。我们还比较了原始CUDA代码和CPU版本的事件处理吞吐量。
英文摘要：
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 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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
