Since the advent of parallel algorithms in the C++17 Standard Template Library (STL), the STL has become a viable framework for creating performance-portable applications. Given multiple existing implementations of the parallel algorithms, a systematic, quantitative performance comparison is essential for choosing the appropriate implementation for a particular hardware configuration. In this work, we introduce a specialized set of micro-benchmarks to assess the scalability of the parallel algorithms in the STL. By selecting different backends, our micro-benchmarks can be used on multi-core systems and GPUs. Using the suite, in a case study on AMD and Intel CPUs and NVIDIA GPUs, we were able to identify substantial performance disparities among different implementations, including GCC+TBB, GCC+HPX, Intel's compiler with TBB, or NVIDIA's compiler with OpenMP and CUDA.
@article{arxiv.2402.06384,
title = {pSTL-Bench: A Micro-Benchmark Suite for Assessing Scalability of C++ Parallel STL Implementations},
author = {Ruben Laso and Diego Krupitza and Sascha Hunold},
journal= {arXiv preprint arXiv:2402.06384},
year = {2024}
}