High-energy physics (HEP) experiments have developed millions of lines of code over decades that are optimized to run on traditional x86 CPU systems. However, we are seeing a rapidly increasing fraction of floating point computing power in leadership-class computing facilities and traditional data centers coming from new accelerator architectures, such as GPUs. HEP experiments are now faced with the untenable prospect of rewriting millions of lines of x86 CPU code, for the increasingly dominant architectures found in these computational accelerators. This task is made more challenging by the architecture-specific languages and APIs promoted by manufacturers such as NVIDIA, Intel and AMD. Producing multiple, architecture-specific implementations is not a viable scenario, given the available person power and code maintenance issues. The Portable Parallelization Strategies team of the HEP Center for Computational Excellence is investigating the use of Kokkos, SYCL, OpenMP, std::execution::parallel and alpaka as potential portability solutions that promise to execute on multiple architectures from the same source code, using representative use cases from major HEP experiments, including the DUNE experiment of the Long Baseline Neutrino Facility, and the ATLAS and CMS experiments of the Large Hadron Collider. This cross-cutting evaluation of portability solutions using real applications will help inform and guide the HEP community when choosing their software and hardware suites for the next generation of experimental frameworks. We present the outcomes of our studies, including performance metrics, porting challenges, API evaluations, and build system integration.

翻译：高能物理实验历经数十年开发了数百万行代码，这些代码经过优化可在传统x86 CPU系统上运行。然而，我们目睹领军级计算设施和传统数据中心中浮点计算能力的占比正快速攀升，其来源主要是新型加速器架构（如GPU）。面对日益主导的计算加速器架构，高能物理实验如今不得不重写数百万行x86 CPU代码，这一前景难以维系。更棘手的是，NVIDIA、英特尔和AMD等厂商推广的架构专用语言与API进一步加剧了挑战。考虑到现有人员配置与代码维护问题，开发多种架构专用实现方案并不可行。高能物理计算卓越中心的便携并行化策略团队正致力于评估Kokkos、SYCL、OpenMP、std::execution::parallel和alpaka等潜在的便携性解决方案——这些方案承诺通过同一源代码在多种架构上执行。团队以主要高能物理实验（包括长基线中微子设施的DUNE实验、大型强子对撞机的ATLAS和CMS实验）的代表性用例为基础开展研究。这项利用真实应用对便携性解决方案进行的跨领域评估，将有助于指导高能物理界为下一代实验框架选择软硬件套件。我们呈现了研究成果，涵盖性能指标、移植挑战、API评估及构建系统集成。