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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Memory-Aware Task Scheduling with Communication Overhead Minimization for Streaming Applications on Bus-Based Multiprocessor System-on-Chips
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Memory-Aware Task Scheduling with Communication Overhead Minimization for Streaming Applications on Bus-Based Multiprocessor System-on-Chips

机译：基于通信开销最小化的内存感知任务调度，用于基于总线的多处理器片上系统上的流应用程序

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摘要

Inter-core communication introduces overheads in task schedules on Multiprocessor System-on-Chips (MPSoCs). Inter-core communication overhead not only negatively impacts the timing performance but also significantly degrades the memory usage for streaming applications running on MPSoC architectures. By minimizing inter-core communication overhead, a shorter period can be applied and system performance (e.g., throughput, memory usage) can be improved. In this paper, we focus on solving the problem of minimizing inter-core communication overhead for streaming applications on bus-based MPSoCs. The objective is to minimize inter-core communication overhead while minimizing the overall memory usage. To solve the problem, we first let tasks with intra-period data dependencies transform to inter-period data dependencies so as to overlap the execution of computation and inter-core communication tasks. By doing this, inter-core communication overhead can be effectively removed. To minimize the overall memory usage, we then perform schedulability analysis and obtain the bounds of the times needed to reschedule each task. Based on the schedulability analysis, we formulate the scheduling problem as an integer linear programming (ILP) model and obtain an optimal schedule. In addition, we propose a heuristic approach to efficiently obtain a near-optimal solution. We conduct experiments on a set of benchmarks from both real-life streaming applications and synthetic task graphs. The experimental results show that the proposed approach can significantly reduce the schedule length and improve the memory usage compared with the previous work.
机译：内核间通信在多处理器片上系统（MPSoC）上的任务计划中引入了开销。内核间通信开销不仅会对时序性能产生负面影响，而且还会大大降低MPSoC架构上运行的流应用程序的内存使用率。通过最小化核心间通信开销，可以应用更短的时间，并且可以改善系统性能（例如，吞吐量，存储器使用率）。在本文中，我们专注于解决基于总线的MPSoC上流应用程序的内核间通信开销最小化的问题。目的是在最大程度减少总体内存使用的同时，最大程度地减少内核间的通信开销。为了解决该问题，我们首先将具有周期内数据依赖性的任务转换为周期内数据依赖性，以使计算和核心间通信任务的执行重叠。通过这样做，可以有效地消除核心间通信开销。为了最大程度地减少整体内存使用量，我们然后进行可调度性分析，并获得重新调度每个任务所需的时间范围。基于可调度性分析，我们将调度问题公式化为整数线性规划（ILP）模型，并获得最佳调度。另外，我们提出了一种启发式方法来有效地获得接近最优的解决方案。我们根据现实生活中的流媒体应用程序和综合任务图在一组基准上进行实验。实验结果表明，与以前的工作相比，该方法可以显着减少调度时间，提高内存使用率。

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