Breeze: User-Level Access to Non-Volatile Main Memories for Legacy Software

Memaripour, Amirsaman; Swanson, Steven

doi:10.1109/iccd.2018.00069

Cited by 17 publications

(13 citation statements)

References 32 publications

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“…Beyond individual data structures, several groups have developed systems to ensure the failure atomicity of lockbased critical sections [3,20,22,32] or speculative transactions [1,4,6,7,9,15,16,37,42,43,48,50]. Significantly, all of these systems ensure that an operation has persisted before permitting the calling thread to proceed-that is, they adopt the strict version of durable linearizability.…”

Section: Related Workmentioning

confidence: 99%

Montage: A General System for Buffered Durably Linearizable Data Structures

Wen,

Cai,

et al. 2020

Preprint

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The recent emergence of fast, dense, nonvolatile main memory suggests that certain long-lived data might remain in its natural pointer-rich format across program runs and hardware reboots. Operations on such data must be instrumented with explicit write-back and fence instructions to ensure consistency in the wake of a crash. Techniques to minimize the cost of this instrumentation are an active topic of research.We present what we believe to be the first general-purpose approach to building buffered durably linearizable persistent data structures, and a system, Montage, to support that approach. Montage is built on top of the Ralloc nonblocking persistent allocator. It employs a slow-ticking epoch clock, and ensures that no operation appears to span an epoch boundary.It also arranges to persist only that data minimally required to reconstruct the structure after a crash. If a crash occurs in epoch e, all work performed in epochs e and e − 1 is lost, but work from prior epochs is preserved.We describe the implementation of Montage, argue its correctness, and report unprecedented throughput for persistent queues, sets/mappings, and general graphs.

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Section: Related Workmentioning

confidence: 99%

Montage: A General System for Buffered Durably Linearizable Data Structures

Wen,

Cai,

et al. 2020

Preprint

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“…First, WSP must be able to restore the entire system on failure recovery no matter how deep the volatile cache and memory hierarchy is as in off-chip DRAM cache as Optane's memory mode. Second, failure recovery should be offered to any programs (instead of being limited to in-memory databases and key-value stores) in a softwaretransparent manner, which is desired as a variety of recent works confirm that persistent programming is error-prone [20,[57][58][59][60][61]67].…”

Section: Motivationmentioning

confidence: 99%

Capri

Jeong

Zeng

Jung

2022

Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing

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This paper investigates whole-system persistence (WSP) that ensures hassle-free crash consistency for all programs while simultaneously leveraging both advantages of the non-volatile memory technologies: high-density and in-memory persistence. Despite the promising characteristics, there are two challenges that must be addressed to make WSP a reality. First, programs must be able to resume the execution from where they had a failure. Second, failure recovery must be offered to any program including the OS in a transparent manner while minimizing persistence overheads.To this end, this paper presents Capri, a compiler and architecture co-designed scheme for region-level whole-system persistence. First, the Capri compiler partitions program into a series of regions whose boundaries serve as recovery points. Then, the Capri architecture provides the regions with crash consistency through hardware-based atomic updates. Finally, with the novel interplay between the architecture and the compiler, Capri provides failure atomicity on the cheap, i.e., with 0%, 12.4%, and 9.1% performance overheads for SPEC CPU2017, STAMP, and Splash3 benchmarks, respectively. CCS CONCEPTS• Hardware → Emerging architectures; Emerging languages and compilers.

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“…This is not a fundamental limitation of Pronto or ASL, but it is necessary to support the easy conversion of volatile data structures into persistent data structures without compiler support. Previous work has shown how to ensure relocatability with a compiler [37]. Those techniques would apply to Pronto.…”

Section: Time Undo Loggingmentioning

confidence: 99%

Pronto

Memaripour

Izraelevitz

Swanson

2020

Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Syste

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Non-Volatile Main Memories (NVMMs) promise an opportunity for fast, persistent data structures. However, building these data structures is hard because their data must be consistent in the wake of a failure. Existing methods for building persistent data structures require either in-depth code changes to an existing data structure using an NVMM-aware library or rewriting the data structure from scratch. Unfortunately, both of these methods are labor-intensive and error-prone. Pronto is a new NVMM library that reduces the programming effort required to add persistence to volatile data structures using asynchronous semantic logging (ASL). ASL is generic enough to allow programmers to add persistence to the existing volatile data structure (e.g., C++ Standard Template Library containers) with very little programming effort. Furthermore, ASL moves most durability code off the critical path, and our evaluation shows Pronto data structures outperform highly-optimized NVMM data structures written with other libraries by a large margin. CCS Concepts. • Hardware → Emerging technologies; • Software and its engineering → Software libraries and repositories; • Information systems → Data structures; • Computer systems organization → Processors and memory architectures.

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Breeze: User-Level Access to Non-Volatile Main Memories for Legacy Software

Cited by 17 publications

References 32 publications

Montage: A General System for Buffered Durably Linearizable Data Structures

Montage: A General System for Buffered Durably Linearizable Data Structures

Capri

Pronto

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