利用与oneAPI的协同执行：现代视角下的异质性
Exploiting co-execution with oneAPI: heterogeneity from a modern perspective
摘要：
由于异构系统体系结构的复杂性，高效地对异构系统进行编程是一个重大挑战。英特尔oneAPI是一种基于SYCL构建的全新的、功能强大的标准统一编程模型，可解决这些问题。在本文中，oneAPI提供了协同执行策略，可以在不同设备之间运行相同的内核，从而可以利用静态和动态策略。在此基础上，对静态和动态负载均衡算法进行了综合分析。这项工作使用集成的GPU和CPU评估了一组众所周知的常规和非常规HPC基准测试的性能和能效。实验结果表明，在使用动态算法时，协同执行是值得的，在使用统一共享内存时，协同执行效率更高。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
