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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Scheduling DAG's for asynchronous multiprocessor execution
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Scheduling DAG's for asynchronous multiprocessor execution

机译：调度DAG以执行异步多处理器

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A new approach is given for scheduling a sequential instruction stream for execution "in parallel" on asynchronous multiprocessors. The key idea in our approach is to exploit the fine grained parallelism present in the instruction stream. In this context, schedules are constructed by a careful balancing of execution and communication costs at the level of individual instructions, and their data dependencies. Three methods are used to evaluate our approach. First, several existing methods are extended to the fine grained situation. Our approach is then compared to these methods using both static schedule length analyses, and simulated executions of the scheduled code. In each instance, our method is found to provide significantly shorter schedules. Second, by varying parameters such as the speed of the instruction set, and the speed/parallelism in the interconnection structure, simulation techniques are used to examine the effects of various architectural considerations on the executions of the schedules. These results show that our approach provides significant speedups in a wide-range of situations. Third, schedules produced by our approach are executed on a two-processor Data General shared memory multiprocessor system. These experiments show that there is a strong correlation between our simulation results, and these actual executions, and thereby serve to validate the simulation studies. Together, our results establish that fine grained parallelism can be exploited in a substantial manner when scheduling a sequential instruction stream for execution "in parallel" on asynchronous multiprocessors.
机译：给出了一种新方法，用于调度顺序指令流以在异步多处理器上“并行”执行。我们方法中的关键思想是利用指令流中存在的细粒度并行性。在这种情况下，通过在各个指令及其数据相关性级别上仔细平衡执行和通信成本来构建时间表。三种方法用于评估我们的方法。首先，将几种现有方法扩展到细粒度情况。然后，使用静态调度长度分析和调度代码的模拟执行，将我们的方法与这些方法进行比较。在每种情况下，我们的方法都可以提供明显更短的时间表。其次，通过改变诸如指令集的速度以及互连结构中的速度/并行度之类的参数，可以使用仿真技术来检查各种体系结构考虑因素对计划执行的影响。这些结果表明，我们的方法可在各种情况下显着提高速度。第三，由我们的方法产生的调度是在两处理器的Data General共享内存多处理器系统上执行的。这些实验表明，我们的仿真结果与这些实际执行之间存在很强的相关性，从而有助于验证仿真研究。总之，我们的结果表明，在调度顺序指令流以在异步多处理器上“并行”执行时，可以以实质性方式利用细粒度并行性。

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