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A General Compiler Framework for Speculative Multithreaded Processors

机译:推测性多线程处理器的通用编译器框架

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摘要

Speculative multithreading (SpMT) promises to be an effective mechanism for parallelizing nonnumeric programs, which tend to have irregular and pointer-intensive data structures and complex flows of control. Proper thread formation is crucial for obtaining good speedup in an SpMT system. This paper presents a compiler framework for partitioning a sequential program into multiple threads for parallel execution in an SpMT system. This framework is very general and supports speculative threads, nonspeculative threads, loop-centric threads, and out-of-order thread spawning. It is therefore useful for compiling for a wide variety of SpMT architectures. For effective partitioning of programs, the compiler uses profiling, interprocedural pointer analysis, data dependence information, and control dependence information. The compiler is implemented on the SUIF-MachSUIF platform. A simulation-based evaluation of the generated threads shows that the use of nonspeculative threads and nonloop speculative threads provides a significant increase in speedup for nonnumeric programs.
机译:推测多线程(SpMT)有望成为一种并行化非数字程序的有效机制,这些程序往往具有不规则且指针密集的数据结构以及复杂的控制流。正确的线程形成对于在SpMT系统中获得良好的加速至关重要。本文提出了一个编译器框架,用于将一个顺序程序划分为多个线程,以便在SpMT系统中并行执行。该框架非常通用,支持推测性线程,非推测性线程,以循环为中心的线程和乱序产生的线程。因此,对于编译各种SpMT架构很有用。为了对程序进行有效的分区,编译器使用概要分析,过程间指针分析,数据相关性信息和控制相关性信息。该编译器在SUIF-MachSUIF平台上实现。对生成的线程的基于仿真的评估表明,使用非推测性线程和非循环推测性线程可以大大提高非数值程序的速度。

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