On the suitability of Ada multitasking for expressing parallel algorithms

S. Yemini
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引用次数: 20

Abstract

This paper examines the suitability of the Ada multitasking model, for supporting parallel algorithms. The algorithms we consider include both SIMD (single instruction multiple data) and MIMD (multiple instruction multiple data) algorithms ([7]). These algorithms are typically used in numerical and other computation-intensive programs, where the ability to take advantage of parallelism available in the supporting hardware, is critical for a program's performance. The multitasking facilities of Ada are shown to lack an essential property necessary to support parallel algorithms: the ability to express parallel evaluation and distribution of parameters to the respective tasks. The resulting serial bottleneck could in certain situations offset the gain from parallelization. Constructs which support parallel evaluation and distribution of parameters to parallel tasks are proposed.
论Ada多任务对并行算法表达的适用性
本文考察了支持并行算法的Ada多任务模型的适用性。我们考虑的算法包括SIMD(单指令多数据)和MIMD(多指令多数据)算法([7])。这些算法通常用于数值和其他计算密集型程序,在这些程序中,利用支持硬件中可用的并行性的能力对程序的性能至关重要。Ada的多任务处理功能缺乏支持并行算法所必需的基本属性:表示并行评估和参数分配到各自任务的能力。在某些情况下,由此产生的串行瓶颈可能抵消并行化带来的增益。提出了支持并行计算和并行任务参数分配的结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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