神经网络多循环路径加速器的设计

Cheol-Won Jo, Kwang-yeob Lee
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引用次数: 0

摘要

MAC计算是神经网络计算中最常用的运算,本文采用multicycle_path来加速MAC计算。当使用管道时,我们不能将操作划分为固定的延迟。因此,退出管道以最低频率确定工作频率。我们提出了一种验证方法,通过使用multicycle_path将操作划分为一定的延时并执行操作,验证了整个过程的操作频率得到了提高。本文的实验分为SingleCycle、Conventional Multicycle、MultiCycle_Ex和MultiCycle_Slice。传统多循环的工作频率是单循环的2.23倍,但资源占用却是单循环的3倍。在保持SingleCycle的资源利用率的情况下,MultiCycle_Ex实现了2.67倍的工作频率,MultiCycle_Slice实现了大约8.2倍的工作频率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of multicycle path accelerator for neural network
In this paper, MAC computation, which is the most used operation in neural network computing, is accelerated by multicycle_path. When using a pipeline, we can not divide the operation into fixed delays. Thus, exiting pipelines determine the operating frequency with the lowest frequency. We proposed the method confirmed that confirmed that the operation frequency of the whole process is improved by using multicycle_path to divide the operation into a certain delay and to perform the operation. In this paper, the experiment was divided into SingleCycle, Conventional Multicycle, MultiCycle_Ex and MultiCycle_Slice. Conventional Multicycle achieved 2.23 times higher operating frequency than SingleCycle, but resource usage tripled. MultiCycle_Ex achieved a 2.67 times higher operating frequency while maintaining the resource usage of SingleCycle, and MultiCycle_Slice achieved operating frequency about 8.2 times higher than SingleCycle.
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