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ReDRAM: A Reconfigurable DRAM Cache for GPGPUs
Date Issued
01-07-2018
Author(s)
Sahoo, Debiprasanna
Sha, Swaraj
Satpathy, Manoranjan
Indian Institute of Technology, Madras
Abstract
Hardware-based DRAM cache techniques for GPGPUs propose to use GPU DRAM as a cache of the host (system) memory. However, these approaches do not exploit the opportunity of allocating store-before-load data (data that is written before being read by GPU cores) on GPU DRAM that would save multiple CPU-GPU transactions. In this context, we propose ReDRAM, a novel memory allocation strategy for GPGPUs which re-configures GPU DRAM cache as a heterogeneous unit. It allows allocation of store-before-load data directly onto GPU DRAM and also utilizes it as a cache of the host memory. Our simulation results using a modified version of GPGPU-Sim show that ReDRAM can improve performance for applications that use store-before-load data by 57.6 percent (avg.) and 4.85x (max.) when compared to the existing proposals on state-of-The-Art GPU DRAM caches.
Volume
17