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We propose ZnG, a new GPU-SSD integrated architecture, which can maximize thememory capacity in a GPU and address performance penalties imposed by an SSD.Specifically, ZnG replaces all GPU internal DRAMs with an ultra-low-latency SSDto maximize the GPU memory capacity. ZnG further removes performance bottleneckof the SSD by replacing its flash channels with a high-throughput flash networkand integrating SSD firmware in the GPU's MMU to reap the benefits of hardwareaccelerations. Although flash arrays within the SSD can deliver highaccumulated bandwidth, only a small fraction of such bandwidth can be utilizedby GPU's memory requests due to mismatches of their access granularity. Toaddress this, ZnG employs a large L2 cache and flash registers to buffer thememory requests. Our evaluation results indicate that ZnG can achieve 7.5xhigher performance than prior work.

ZnG: Architecting GPU Multi-Processors with New Flash for Scalable Data Analysis