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Accelerating sparse matrix-matrix multiplication with 3D-stacked logic-in-memory hardware

机译:利用3D堆叠的内存中逻辑硬件加速稀疏矩阵矩阵乘法

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This paper introduces a 3D-stacked logic-in-memory (LiM) system to accelerate the processing of sparse matrix data that is held in a 3D DRAM system. We build a customized content addressable memory (CAM) hardware structure to exploit the inherent sparse data patterns and model the LiM based hardware accelerator layers that are stacked in between DRAM dies for the efficient sparse matrix operations. Through silicon vias (TSVs) are used to provide the required high inter-layer bandwidth. Furthermore, we adapt the algorithm and data structure to fully leverage the underlying hardware capabilities, and develop the necessary design framework to facilitate the design space evaluation and LiM hardware synthesis. Our simulation demonstrates more than two orders of magnitude of performance and energy efficiency improvements compared with the traditional multithreaded software implementation on modern processors.
机译:本文介绍了一种3D堆栈式内存逻辑(LiM)系统,以加快处理3D DRAM系统中保存的稀疏矩阵数据的速度。我们构建了一个定制的内容可寻址存储器(CAM)硬件结构,以利用固有的稀疏数据模式,并对基于LiM的硬件加速器层进行建模,这些层堆叠在DRAM裸片之间,以实现有效的稀疏矩阵操作。穿硅通孔(TSV)用于提供所需的高层间带宽。此外,我们调整算法和数据结构以充分利用基础硬件功能,并开发必要的设计框架以促进设计空间评估和LiM硬件综合。与在现代处理器上的传统多线程软件实现相比,我们的仿真证明了性能和能效方面的改进超过了两个数量级。

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