2020/06/16 by Jie Zhang, Zhang, Jie, Myoungsoo Jung +1 · 1 citation
Computer Science · #FOS: Computer and information sciences #Hardware Architecture (cs.AR) #cs.AR
paper · pdf · doi:10.48550/arxiv.2006.08975
arxiv created 2020/06/16 · arxiv updated 2020/06/17
We propose ZnG, a new GPU-SSD integrated architecture, which can maximize the memory capacity in a GPU and address performance penalties imposed by an SSD. Specifically, ZnG replaces all GPU internal DRAMs with an ultra-low-latency SSD to maximize the GPU memory capacity. ZnG further removes performance bottleneck of the SSD by replacing its flash channels with a high-throughput flash network and integrating SSD firmware in the GPU's MMU to reap the benefits of hardware accelerations. Although flash arrays within the SSD can deliver high accumulated bandwidth, only a small fraction of such bandwidth can be utilized by GPU's memory requests due to mismatches of their access granularity. To address this, ZnG employs a large L2 cache and flash registers to buffer the memory requests. Our evaluation results indicate that ZnG can achieve 7.5x higher performance than prior work.