With the increasing amount of optimized and specialized hardware such as GPUs, ML cores, etc. HEP applications face the opportunity and the challenge of adapting to efficiently use these resources, which are becoming more widely available on scientific computing sites. The Heterogeneous Frameworks project aims at evaluating new methods and tools for the support of both heterogeneous computational nodes and multi node workloads. Based on the experience from the parallel frameworks of the LHC experiments and their ad-hoc support for heterogeneous resources, this project investigates newer libraries and languages that have been developed after the move to parallel frameworks about a decade ago. This paper summarizes the scope of the problem being tackled, the state of the art of heterogeneous libraries, and the benchmark infrastructure used for the R&D activities. We present as well some of the tooling developed to extract the benchmark scenarios from existing LHC experiment workflows. The first results of using both newer C++ and Julia libraries for parallel execution are shown.
Fila et al. (Tue,) studied this question.