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Library Support for Resource Constrained Accelerators

机译:资源受限加速器的库支持

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Accelerators, and other resource constrained systems, are increasingly being used in computer systems. Accelerators provide power efficient performance and often provide a shared memory model. However, it is a challenge to map feature rich APIs, such as OpenMP, to resource constrained systems. In this paper, we present a lightweight system where an accelerator can remotely execute library functions on a host processor. The implementation takes up 750 bytes but can replace arbitrary library calls leading to significant savings in memory foot print. We evaluate with a set of SPLASH-2 applications and show that the impact on execution time is negligible when compared to GCCs OpenMP implementation.
机译:加速器和其他资源受限的系统正越来越多地用于计算机系统中。加速器可提供省电的性能,并且通常提供共享的内存模型。但是,将功能丰富的API(例如OpenMP)映射到资源受限的系统是一个挑战。在本文中,我们提出了一个轻量级的系统,其中加速器可以在主机处理器上远程执行库函数。该实现占用750个字节,但可以替换任意的库调用,从而显着节省了内存占用空间。我们对一组SPLASH-2应用程序进行了评估,结果表明,与GCC的OpenMP实施相比,对执行时间的影响可以忽略不计。

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