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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,但作为以减少它的执行等待时间并行执行单个应用程序的车辆。本文礼物血统,编译工具,它采用了基于程序依赖图(PDG)一个新的分区启发。 PEDIGREE将创建重叠相互依赖线程,对SMP的处理器即游行线程的可用的并行的子集每个执行。一个统一的框架用于构建从程序,循环嵌套,循环迭代,以及更小的结构线。 PEDIGREE不需要任何并行语言的支持;这是一个后编译工具,在目标代码读取。所述SDIO信号和数据处理基准套件已经被选择作为实时,延迟敏感代码的例子。其粗粒度数据流并行操作受PEDIGREE利用分别达到1.56倍的/ 2.11x(平均值/最大值)和1.61x / 2.60x加速比在两个和四个处理器。有大约超过该只利用数据并行现有技术提高15%。通过利用对于粗粒流水线数据的单向流动,所述同步开销通常限于小于6%进行100个循环的同步延迟时间,以及10个循环低于2%。

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