Characterizing the performance of intel optane persistent memory

Lingfeng Xiang, Xingsheng Zhao, Jia Rao, Song Jiang, Hong Jiang
2022 Proceedings of the Seventeenth European Conference on Computer Systems  
We present a comprehensive and in-depth study of Intel Optane DC persistent memory (DCPMM). Our focus is on exploring the internal design of Optane's on-DIMM readwrite buffering and its impacts on application-perceived performance, read and write amplifications, the overhead of different types of persists, and the tradeoffs between persistency models. While our measurements confirm the results of the existing profiling studies, we have new discoveries and offer new insights. Notably, we find
more » ... t read and write are managed differently in separate on-DIMM read and write buffers. Comparable in size, the two buffers serve distinct purposes. The read buffer offers higher concurrency and effective on-DIMM prefetching, leading to high read bandwidth and superior sequential performance. However, it does not help hide media access latency. In contrast, the write buffer offers limited concurrency but is a critical stage in a pipeline that supports asynchronous write in the DDR-T protocol. Surprisingly, in addition to write coalescing, the write buffer delivers lower than read and consistent write latency regardless of the working set size, the type of write, the access pattern, or the persistency model. Furthermore, we discover that the mismatch between cacheline access granularity and the 3D-Xpoint media access granularity negatively impacts the effectiveness of CPU cache prefetching and leads to wasted persistent memory bandwidth. Our proposition is to decouple read and write in the performance analysis and optimization of persistent programs. We present three case studies based on this insight and demonstrate considerable performance improvements. We verify the results on two generations of Optane DCPMM.
doi:10.1145/3492321.3519556 fatcat:kqewpy3xzbhcxctxnax2xl6jmy