GraphiDe: A Graph Processing Accelerator leveraging In-DRAM-Computing
GraphiDe: A Graph Processing Accelerator leveraging In-DRAM-Computing
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DOI：
10.1145/3299874.3317984
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发表时间：
2019-05
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影响因子：
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通讯作者：
Shaahin Angizi;Deliang Fan
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文献类型：
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作者：
Shaahin Angizi;Deliang Fan
在本文中，我们提出了GraphiDe，一种新的DRAM为基础的内存处理（PIM）加速器的图形处理。它将当前的DRAM架构转换为大规模并行计算单元，利用现代存储芯片的高内部带宽来加速各种图形处理应用。GraphiDe可以通过消除不必要的片外访问来大大减少处理底层邻接矩阵计算的能耗和延迟。在三个社交网络数据集上进行的广泛的电路架构模拟表明，GraphiDe与最近基于DRAM的PIM平台相比，平均实现了3.1倍的能效提升和4.2倍的速度提升。与基于GPU的加速方法相比，它实现了约59倍的能效和83倍的加速。
In this paper, we propose GraphiDe, a novel DRAM-based processing-in-memory (PIM) accelerator for graph processing. It transforms current DRAM architecture to massively parallel computational units exploiting the high internal bandwidth of the modern memory chips to accelerate various graph processing applications. GraphiDe can be leveraged to greatly reduce energy consumption and latency dealing with underlying adjacency matrix computations by eliminating unnecessary off-chip accesses. The extensive circuit-architecture simulations over three social network data-sets indicate that GraphiDe achieves on average 3.1x energy-efficiency improvement and 4.2x speed-up over the recent DRAM based PIM platform. It achieves ~59x higher energy-efficiency and 83x speed-up over GPU-based acceleration methods.