Abstract
Portable and efficient vectorization is a significant challenge in large software projects such as GeantV, ROOT, and experiments’ frameworks. Nevertheless, fully exploiting SIMD parallelism will be a required step in order to bridge the widening gap between the needs and availability of computing resouces for data analysis and processing in particle physics. Although there are SIMD libraries that wrap compiler intrinsics into a convenient interface, they do not always support all available architectures, or they only perform well in some of them. The VecCore library was created to address some of these performance and portability issues by providing a unified abstraction layer on top of existing libraries, such as Vc or UME::SIMD. In this article, we discuss VecCore’s programming model for SIMD code and some use cases in HEP software packages such as VecGeom and GeantV.
Highlights
Experiments at CERN have an ever increasing demand for computational resources, be it for simulated collisions or data analysis
Portable and efficient vectorization is a significant challenge in large software projects such as GeantV, ROOT, and experiments’ frameworks
One of the key areas through which performance can be substantially improved in HEP software is SIMD vectorization
Summary
Experiments at CERN have an ever increasing demand for computational resources, be it for simulated collisions or data analysis. The VecCore library was created to address some of these performance and portability issues by providing a unified abstraction layer on top of existing libraries, such as Vc or UME::SIMD.
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