An early evaluation of Intel's optane DC persistent memory module and its impact on high-performance scientific applications

Non-volatile memory and remote direct memory access (RDMA) provide extremely high performance in storage and network hardware. However, existing distributed file systems strictly isolate file system and network layers, and the heavy layered software designs leave high-speed hardware under-exploited. In this article, we propose an RDMA-enabled distributed persistent memory file system, Octopus + , to redesign file system internal mechanisms by closely coupling non-volatile memory and RDMA features. For data operations, Octopus + directly accesses a shared persistent memory pool to reduce memory copying overhead, and actively fetches and pushes data all in clients to rebalance the load between the server and network. For metadata operations, Octopus + introduces self-identified remote procedure calls for immediate notification between file systems and networking, and an efficient distributed transaction mechanism for consistency. Octopus + is enabled with replication feature to provide better availability. Evaluations on Intel Optane DC Persistent Memory Modules show that Octopus + achieves nearly the raw bandwidth for large I/Os and orders of magnitude better performance than existing distributed file systems.

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Revisiting the design of LSM-tree Based OLTP storage engine with persistent memory

Proceedings of the VLDB Endowment ◽

10.14778/3467861.3467875 ◽

2021 ◽

Vol 14 (10) ◽

pp. 1872-1885

Author(s):

Baoyue Yan ◽

Xuntao Cheng ◽

Bo Jiang ◽

Shibin Chen ◽

Canfang Shang ◽

...

Keyword(s):

Recovery Time ◽

High Performance ◽

Transaction Processing ◽

Light Weight ◽

Global Index ◽

Persistent Memory ◽

Write Amplification ◽

Database As A Service ◽

Overall Evaluation ◽

Memory Compaction

The recent byte-addressable and large-capacity commercialized persistent memory (PM) is promising to drive database as a service (DBaaS) into unchartered territories. This paper investigates how to leverage PMs to revisit the conventional LSM-tree based OLTP storage engines designed for DRAM-SSD hierarchy for DBaaS instances. Specifically we (1) propose a light-weight PM allocator named Hal-loc customized for LSM-tree, (2) build a high-performance Semi-persistent Memtable utilizing the persistent in-memory writes of PM, (3) design a concurrent commit algorithm named Reorder Ring to aschieve log-free transaction processing for OLTP workloads and (4) present a Global Index as the new globally sorted persistent level with non-blocking in-memory compaction. The design of Reorder Ring and Semi-persistent Memtable achieves fast writes without synchronized logging overheads and achieves near instant recovery time. Moreover, the design of Semi-persistent Memtable and Global Index with in-memory compaction enables the byte-addressable persistent levels in PM, which significantly reduces the read and write amplification as well as the background compaction overheads. The overall evaluation shows that the performance of our proposal over PM-SSD hierarchy outperforms the baseline by up to 3.8x in YCSB benchmark and by 2x in TPC-C benchmark.

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Persistent memory hash indexes

Proceedings of the VLDB Endowment ◽

10.14778/3446095.3446101 ◽

2021 ◽

Vol 14 (5) ◽

pp. 785-798

Author(s):

Daokun Hu ◽

Zhiwen Chen ◽

Jianbing Wu ◽

Jianhua Sun ◽

Hao Chen

Keyword(s):

Future Development ◽

High Performance ◽

Performance Metrics ◽

Comprehensive Evaluation ◽

State Of The Art ◽

Hash Tables ◽

Trade Offs ◽

Depth Analysis ◽

Persistent Memory ◽

Memory Modules

Persistent memory (PM) is increasingly being leveraged to build hash-based indexing structures featuring cheap persistence, high performance, and instant recovery, especially with the recent release of Intel Optane DC Persistent Memory Modules. However, most of them are evaluated on DRAM-based emulators with unreal assumptions, or focus on the evaluation of specific metrics with important properties sidestepped. Thus, it is essential to understand how well the proposed hash indexes perform on real PM and how they differentiate from each other if a wider range of performance metrics are considered. To this end, this paper provides a comprehensive evaluation of persistent hash tables. In particular, we focus on the evaluation of six state-of-the-art hash tables including Level hashing, CCEH, Dash, PCLHT, Clevel, and SOFT, with real PM hardware. Our evaluation was conducted using a unified benchmarking framework and representative workloads. Besides characterizing common performance properties, we also explore how hardware configurations (such as PM bandwidth, CPU instructions, and NUMA) affect the performance of PM-based hash tables. With our in-depth analysis, we identify design trade-offs and good paradigms in prior arts, and suggest desirable optimizations and directions for the future development of PM-based hash tables.

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