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A Case for Hardware Task Management Support for the StarSS Programming Model

机译:对StarS编程模型的硬件任务管理支持的案例

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StarSS is a parallel programming model that eases the task of the programmer. He or she has to identify the tasks that can potentially be executed in parallel and the inputs and outputs of these tasks, while the runtime system takes care of the difficult issues of determining inter task dependencies, synchronization, load balancing, scheduling to optimize data locality, etc. Given these issues, however, the runtime system might become a bottleneck that limits the scalability of the system. The contribution of this paper is two-fold. First, we analyze the scalability of the current software runtime system for several synthetic benchmarks with different dependency patterns and task sizes. We show that for fine-grained tasks the system does not scale beyond five cores. Furthermore, we identify the main scalability bottlenecks of the runtime system. Second, we present the design of Nexus, a hardware support system for StarSS applications, that greatly reduces the task management overhead.
机译:StarSS是一种并行编程模型,可简化程序员的工作。他或她必须确定可能并行执行的任务以及这些任务的输入和输出,而运行时系统则要处理确定任务间依赖关系,同步,负载平衡,计划以优化数据局部性的难题。但是,鉴于这些问题,运行时系统可能成为限制系统可伸缩性的瓶颈。本文的贡献是双重的。首先,我们针对具有不同依赖模式和任务大小的几个综合基准,分析当前软件运行时系统的可伸缩性。我们表明,对于细粒度的任务,系统的扩展范围不会超过五个核心。此外,我们确定了运行时系统的主要可伸缩性瓶颈。其次,我们介绍Nexus的设计,该产品是用于StarSS应用程序的硬件支持系统,可大大减少任务管理的开销。

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