Exploiting co-execution with oneAPI: heterogeneity from a modern perspective
Department of Computer Science and Electronics, Universidad de Cantabria, Spain
arXiv:2106.01726 [cs.DC], (3 Jun 2021)
@misc{nozal2021exploiting,
title={Exploiting co-execution with oneAPI: heterogeneity from a modern perspective},
author={Raúl Nozal and Jose Luis Bosque},
year={2021},
eprint={2106.01726},
archivePrefix={arXiv},
primaryClass={cs.DC}
}
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.
June 6, 2021 by hgpu
