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Efficient GPU NVRAM Persistence with Helper Warps

机译:借助辅助扭曲实现高效的GPU NVRAM持久性

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Non-volatile Random-Access Memories (NVRAM) have emerged in recent years to bridge the performance gap between the main memory and external storage devices. To utilize the non-volatility of NVRAMs, programs should allow durable stores, meaning consistency must be maintained during a power loss event. GPUs are designed with high throughput, leveraging high degrees of parallelism. However, with lower NVRAM write bandwidths compared to that of DRAMs, using NVRAM as is may yield suboptimal overall system performance. To address this problem, we propose using Helper Warps to move persistence out of the critical path of transaction execution, alleviating the impact of latencies. Our mechanism achieves a speedup of 4.4 and 1.5 under bandwidth limits of 1.6 GB/s and 12 GB/s and is projected to maintain speed advantage even when NVRAM bandwidth gets as high as hundreds of GB/s in certain cases.
机译:近年来,出现了非易失性随机存取存储器(NVRAM),以弥合主存储器和外部存储设备之间的性能差距。为了利用NVRAM的非易失性,程序应允许持久存储,这意味着在断电事件期间必须保持一致性。 GPU设计为具有高吞吐量,并利用了高度的并行性。但是,与DRAM相比,由于NVRAM的写入带宽较低,因此按原样使用NVRAM可能会导致整体系统性能欠佳。为了解决此问题,我们建议使用Helper Warps将持久性移出事务执行的关键路径,从而减轻延迟的影响。我们的机制在1.6 GB / s和12 GB / s的带宽限制下实现了4.4和1.5的加速,并且即使在某些情况下,即使NVRAM带宽高达数百GB / s,也有望保持速度优势。

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