Over the last decade, most of the increase in computing power has been gained
by advances in accelerated many-core architectures, mainly in the form of
GPGPUs. While accelerators achieve phenomenal performances in various computing
tasks, their utilization requires code adaptations and transformations. Thus,
OpenMP, the most common standard for multi-threading in scientific computing
applications, introduced offloading capabilities between host (CPUs) and
accelerators since v4.0, with increasing support in the successive v4.5, v5.0,
v5.1, and the latest v5.2 versions. Recently, two state-of-the-art GPUs - the
Intel Ponte Vecchio Max 1100 and the NVIDIA A100 GPUs - were released to the
market, with the oneAPI and GNU LLVM-backed compilation for offloading,
correspondingly. In this work, we present early performance results of OpenMP
offloading capabilities to these devices while specifically analyzing the
potability of advanced directives (using SOLLVE's OMPVV test suite) and the
scalability of the hardware in representative scientific mini-app (the LULESH
benchmark). Our results show that the vast majority of the offloading
directives in v4.5 and 5.0 are supported in the latest oneAPI and GNU
compilers; however, the support in v5.1 and v5.2 is still lacking. From the
performance perspective, we found that PVC is up to 37% better than the A100 on
the LULESH benchmark, presenting better performance in computing and data
movements.Comment: 13 page