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Computer systems utilizing byte-addressable Non-Volatile Memory ( NVM ) as memory/storage can provide low-latency data persistence. The widely used key-value stores using Log-Structured Merge Tree ( LSM-Tree ) are still beneficial for NVM systems in aspects of the space and write efficiency. However, the significant write amplification introduced by the leveled compaction of LSM-Tree degrades the write performance of the key-value store and shortens the lifetime of the NVM devices. The existing studies propose new compaction methods to reduce write amplification. Unfortunately, they result in a relatively large read amplification. In this article, we propose NVLSM, a key-value store for NVM systems using LSM-Tree with new accumulative compaction. By fully utilizing the byte-addressability of NVM, accumulative compaction uses pointers to accumulate data into multiple floors in a logically sorted run to reduce the number of compactions required. We have also proposed a cascading searching scheme for reads among the multiple floors to reduce read amplification. Therefore, NVLSM reduces write amplification with small increases in read amplification. We compare NVLSM with key-value stores using LSM-Tree with two other compaction methods: leveled compaction and fragmented compaction. Our evaluations show that NVLSM reduces write amplification by up to 67% compared with LSM-Tree using leveled compaction without significantly increasing the read amplification. In write-intensive workloads, NVLSM reduces the average latency by 15.73%–41.2% compared to other key-value stores.
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HOOP: Efficient Hardware-Assisted Out-of-Place Update for Non-Volatile Memory
Byte-addressable non-volatile memory (NVM) is a promising technology that provides near-DRAM performance with scalable memory capacity. However, it requires atomic data durability to ensure memory persistency. Therefore, many techniques, including logging and shadow paging, have been proposed. However, most of them either introduce extra write traffic to NVM or suffer from significant performance overhead on the critical path of program execution, or even both. In this paper, we propose a transparent and efficient hardware-assisted out-of-place update (HOOP) mechanism that supports atomic data durability, without incurring much extra writes and performance overhead. The key idea is to write the updated data to a new place in NVM, while retaining the old data until the updated data becomes durable. To support this, we develop a lightweight indirection layer in the memory controller to enable efficient address translation and adaptive garbage collection for NVM. We evaluate HOOP with a variety of popular data structures and data-intensive applications, including key-value stores and databases. Our evaluation shows that HOOP achieves low critical-path latency with small write amplification, which is close to that of a native system without persistence support. Compared with state-of-the-art crash-consistency techniques, it improves application performance by up to 1.7×, while reducing the write amplification by up to 2.1×. HOOP also demonstrates scalable data recovery capability on multi-core systems.
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- PAR ID:
- 10195216
- Date Published:
- Journal Name:
- 2020 ACM/IEEE 47th Annual International Symposium on Computer Architecture (ISCA)
- Page Range / eLocation ID:
- 584 to 596
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ISCA45697.2020.00055
