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Memory-Access-Driven Context Partitioning tor Window-Based Image Processing on Heterogeneous Multicore Processors

机译:异构多核处理器上基于内存的存储器驱动上下文分割或基于窗口的图像处理

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摘要

Accelerator cores in low-power heterogeneous processors have on-chip local memories to enable parallel data access. The memory capacities of the local memories are very small. Therefore, the data should be transferred from the global memory to the local memories many times. These data transfers greatly increase the total processing time. Memory allocation technique to increase the data sharing is a good solution to this problem. However, when using reconfigurable cores, the data must be shared among multiple contexts. However, conventional context partitioning methods only consider how to reuse limited hardware resources in different time slots. They do not consider the data sharing. This paper proposes a context partitioning method to share both the hardware resources and the local memory data. According to the experimental results, the proposed method reduces the processing time by more than 87% compared to conventional context partitioning techniques.
机译:低功耗异构处理器中的加速器内核具有片上本地存储器,以实现并行数据访问。本地存储器的存储容量很小。因此,数据应多次从全局存储器传输到本地存储器。这些数据传输大大增加了总处理时间。使用内存分配技术来增加数据共享是解决此问题的好方法。但是,使用可重配置内核时,必须在多个上下文之间共享数据。但是,传统的上下文分区方法仅考虑如何在不同的时隙中重用有限的硬件资源。他们不考虑数据共享。本文提出了一种上下文分割方法来共享硬件资源和本地内存数据。根据实验结果,与传统的上下文划分技术相比,该方法将处理时间减少了87%以上。

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