IRIS-BLAS:迈向性能可移植和异构的BLAS库

2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC) Pub Date : 2022-12-01 DOI:10.1109/HiPC56025.2022.00042

Narasinga Rao Miniskar, Mohammad Alaul Haque Monil, Pedro Valero-Lara, Frank Liu, J. Vetter

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引用次数: 3

摘要

IRIS-BLAS是一种新型的异构、高性能便携式BLAS库。IRIS-BLAS建立在IRIS运行时和多个供应商和开源的BLAS库之上。它可以透明地使用异构系统中可用的所有体系结构/设备，在运行时使用基于任务映射的适当BLAS库。因此，IRIS-BLAS可以在广泛的体系结构和BLAS库之间移植，减轻了应用程序开发人员对修改应用程序源代码的担忧。尽管重点是便携性，但IRIS-BLAS提供了比其他最先进的参考产品更具竞争力甚至更好的性能。此外，IRIS-BLAS还提供了一些新功能，例如有效地使用由来自不同硬件供应商的多个gpu组成的极端异构系统。

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IRIS-BLAS: Towards a Performance Portable and Heterogeneous BLAS Library

This paper presents IRIS-BLAS, a novel heterogeneous and performance portable BLAS library. IRIS-BLAS is built on top of the IRIS runtime and multiple vendor and open-source BLAS libraries. It can transparently use all the architectures/devices available in a heterogeneous system, using the appropriate BLAS library based on the task mapping at run time. Thus, IRIS-BLAS is portable across a broad spectrum of architectures and BLAS libraries, alleviating the worry of application developers about modifying the application source code. Even though the emphasis is on portability, IRIS-BLAS provides competitive or even better performance than other state-of-the-art references. Moreover, IRIS-BLAS offers new features such as efficiently using extremely heterogeneous systems composed of multiple GPUs from different hardware vendors.

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来源期刊

2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)

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