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Automatic partitioning of signal processing programs for symmetric multiprocessors

机译:对称多处理器信号处理程序的自动分区

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Symmetric multiprocessor systems are increasingly common, not only as servers, but as a vehicle for executing a single application in parallel in order to reduce its execution latency. This paper presents PEDIGREE, a compilation tool that employs a new partitioning heuristic based on the program dependence graph (PDG). PEDIGREE creates overlapping inter-dependent threads, each executing on a subset of the SMP's processors that marches the thread's available parallelism. A unified framework is used to build threads from procedures, loop nests, loop iterations, and smaller constructs. PEDIGREE does not require any parallel language support; it is a post-compilation tool that reads in object code. The SDIO Signal and Data Processing Benchmark Suite has been selected as an example of real-time, latency-sensitive code. Its coarse-grained data flow parallelism is exploited by PEDIGREE to achieve speedups of 1.56x/2.11x (mean/max) and 1.61x/2.60x on two and four processors, respectively. There is roughly a 15% improvement over existing techniques that exploit only data parallelism. By exploiting the unidirectional flow of data for coarse-grained pipelining, the synchronization overhead is typically limited to less than 6% for synchronization latency of 100 cycles, and less than 2% for 10 cycles.
机译:对称多处理器系统越来越普遍,不仅作为服务器,而且作为并行执行单个应用程序以减少其执行延迟的手段。本文介绍了PEDIGREE,这是一种基于程序依赖图(PDG)采用新分区启发式方法的编译工具。 PEDIGREE创建重叠的相互依赖的线程,每个线程都在SMP处理器的子集上执行,该处理器将线程的可用并行性进行调整。统一的框架用于从过程,循环嵌套,循环迭代和较小的构造中构建线程。 PEDIGREE不需要任何并行语言支持;它是一个后编译工具,可读取目标代码。已选择SDIO信号和数据处理基准套件作为实时,延迟敏感代码的示例。 PEDIGREE利用其粗粒度的数据流并行性在两个和四个处理器上分别实现了1.56x / 2.11x(平均/最大)和1.61x / 2.60x的加速。与仅利用数据并行性的现有技术相比,大约有15%的改进。通过将数据的单向流用于粗粒度流水线,对于100个周期的同步延迟,同步开销通常被限制为小于6%,而对于10个周期的同步开销则被限制为小于2%。

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