为不同的计算机体系结构设计线性代数算法

J. Dongarra
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引用次数: 0

摘要

未来机器的架构承诺提供丰富的计算环境。现有的先驱已经给了许多软件开发人员重新检查底层算法以提高效率的理由。然而,只考虑一台计算机来重铸算法似乎是一种不必要的浪费,不管这台计算机有多快。由于使用或提出的计算机系统和体系结构种类繁多,设计算法的人面临的挑战是开发出既高效又可移植的算法和最终的软件。在本次演讲中,我们将讨论几种基于高级模块的线性代数标准算法在高性能计算机上的实现和性能,如CRAY 1、CRAY X-MP、富士通VP-200、日立S-810/20和德耐尔HEP。高级模块化促进了可移植性,并有助于在跨越标量、矢量和某些并行计算机的各种环境中实现性能效率。
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Designing algorithms in linear algebra for different computer architectures
Architectures of future machines promise to offer a profusion of computing environments. The existing forerunners have already given many software developers cause to reexamine the underlying algorithms for efficiency sake. However, it seems to be an unnecessary waste of effort to recast algorithms with only one computer in mind, regardless of how fast that one may be. With such a wide variety of computer systems and architectures in use or proposed, the challenge for people designing algorithms is to develop algorithms and ultimately software that are both efficient and portable. In this talk we will discuss implementations and performance of a few standard algorithms from linear algebra on high performance computers, such as the CRAY 1, CRAY X-MP, Fujitsu VP-200, Hitachi S-810/20 and Denelcor HEP based on the use of high-level modules. High-level modularity facilitates portability and aids in attaining performance efficiency on a wide variety of environments spanning scalar, vector, and certain parallel computers.
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