Compiling MATLAB programs to ScaLAPACK: exploiting task and data parallelism
Compiling MATLAB programs to ScaLAPACK: exploiting task and data parallelism
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将 MATLAB 程序编译为 ScaLAPACK：利用任务和数据并行性
DOI：
10.1109/ipps.1996.508120
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发表时间：
1996
期刊：
影响因子：
--
通讯作者：
P. Banerjee
中科院分区：
文献类型：
--
作者：
S. Ramaswamy;IV EugeneW.Hodges;P. Banerjee
我们提出了一种新的方法，旨在减少所需的努力，分布式内存多计算机编程。在我们的方法中的关键思想是自动转换的基于库的编程语言（MATLAB）编写的程序的ScaLAPACK并行库的基础上的并行程序。在执行此转换的过程中，我们应用编译器优化，同时利用任务和数据并行。正如我们的结果表明，我们的方法是可行的和实用的，我们的优化提供了显着的性能优势。
We suggest a new approach aimed at reducing the effort required to program distributed-memory multicomputers. The key idea in our approach is to automatically convert a program written in a library-based programming language (MATLAB) to a parallel program based on the ScaLAPACK parallel library. In the process of performing this conversion, we apply compiler optimizations that simultaneously exploit task and data parallelism. As our results show, our approach is feasible and practical and our optimization provides significant performance benefits.