Programming efficiently heterogeneous systems is a major challenge, due to the complexity of their architectures. Intel oneAPI, a new and powerful standards-based unified programming model, built on top of SYCL, addresses these issues. In this paper, oneAPI is provided with co-execution strategies to run the same kernel between different devices, enabling the exploitation of static and dynamic policies. On top of that, static and dynamic load-balancing algorithms are integrated and analyzed. This work evaluates the performance and energy efficiency for a well-known set of regular and irregular HPC benchmarks, using an integrated GPU and CPU. Experimental results show that co-execution is worthwhile when using dynamic algorithms, improving efficiency even more when using unified shared memory.
@article{arxiv.2106.01726,
title = {Exploiting co-execution with oneAPI: heterogeneity from a modern perspective},
author = {Raúl Nozal and Jose Luis Bosque},
journal= {arXiv preprint arXiv:2106.01726},
year = {2021}
}
Comments
Accepted in Euro-Par 2021 (27th International Conference on Parallel and Distributed Computing). 16 pages, 9 figures, 1 listing. Conference paper - extended with API