Clobber-NVM: log less, re-execute more

Xu, Yi; Izraelevitz, Joseph; Swanson, Steven

doi:10.1145/3445814.3446730

Cited by 19 publications

(3 citation statements)

References 51 publications

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“…A lot of work has been devoted to design persistent transactional memory systems (e.g., [53,14,13,44,34,45,8,55,39]). Such systems often rely on some kind of logging technique employing either redo logs [53,34,45] or undo logs [13,44,14 penalties as the log is usually stored in persistent memory.…”

Section: Related Workmentioning

confidence: 99%

The performance power of software combining in persistence

Fatourou

Kallimanis

Kosmas

2022

Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

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The availability of Non-Volatile Main Memory (known as NVMM) enables the design of recoverable concurrent algorithms. We study the power of software combining in achieving recoverable synchronization and designing persistent data structures. Software combining is a general synchronization approach, which attempts to simulate the ideal world when executing synchronization requests (i.e., requests that must be executed in mutual exclusion). A single thread, called the combiner, executes all active requests, while the rest of the threads are waiting for the combiner to notify them that their requests have been applied. Software combining significantly decreases the synchronization cost and outperforms many other synchronization techniques in various cases.We identify three persistence principles, crucial for performance, that an algorithm's designer has to take into consideration when designing highly-efficient recoverable synchronization protocols or data structures. We illustrate how to make the appropriate design decisions in all stages of devising recoverable combining protocols to respect these principles. Specifically, we present two recoverable software combining protocols, satisfying different progress properties, that are many times faster and have much lower persistence cost than a large collection of existing persistent techniques for achieving scalable synchronization. We build fundamental recoverable data structures, such as stacks and queues, based on these protocols that outperform by far existing recoverable implementations of such data structures. We also provide the first recoverable implementation of a concurrent heap and present experiments to show that it has good performance when the size of the heap is not very large.

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Section: Related Workmentioning

confidence: 99%

The performance power of software combining in persistence

Fatourou

Kallimanis

Kosmas

2022

Proceedings of the 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

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“…For example, memcached-pmem [13] rebuilds the LRU cache and the hash table from persistent slabs (i.e., persistent storage of inserted key-value items), which implicitly fixes some of the data inconsistencies found by PMRace and recent work [15] (e.g., inconsistencies limited to the łnextž and łprevž fields of items are automatically fixed due to the index rebuilding), thus causing false positives. Another example is undo logging [11,62] based transactions (e.g., PMDK), which copy old consistent data via write-ahead logging before transaction executions. During the recovery of uncommitted transactions, the data modified in transactions are reverted to the old consistent version from previous logs.…”

Section: Post-failure Validationmentioning

confidence: 99%

Efficiently detecting concurrency bugs in persistent memory programs

Chen

Hua

Zhang

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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Due to the salient DRAM-comparable performance, TB-scale capacity, and non-volatility, persistent memory (PM) provides new opportunities for large-scale in-memory computing with instant crash recovery. However, programming PM systems is error-prone due to the existence of crash-consistency bugs, which are challenging to diagnose especially with concurrent programming widely adopted in PM applications to exploit hardware parallelism. Existing bug detection tools for DRAM-based concurrency issues cannot detect PM crash-consistency bugs because they are oblivious to PM operations and PM consistency. On the other hand, existing PM-specific debugging tools only focus on sequential PM programs and cannot effectively detect crash-consistency issues hidden in concurrent executions.In order to effectively detect crash-consistency bugs that only manifest in concurrent executions, we propose PMRace, the first PM-specific concurrency bug detection tool. We identify and define two new types of concurrent crash-consistency bugs: PM Interthread Inconsistency and PM Synchronization Inconsistency. In particular, PMRace adopts PM-aware and coverage-guided fuzz testing to explore PM program executions. For PM Inter-thread Inconsistency, which denotes the data inconsistency hidden in thread interleavings, PMRace performs PM-aware interleaving exploration and thread scheduling to drive the execution towards executions that reveal such inconsistencies. For PM Synchronization Inconsistency between persisted synchronization variables and program data, PM-Race identifies the inconsistency during interleaving exploration. The post-failure validation reduces the false positives that come from custom crash recovery mechanisms. PMRace has found 14 bugs (10 new bugs) in real-world concurrent PM systems including PM-version memcached.

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“…There is a great deal of work on building programming systems that allow developers to use PM in a reliable way without knowing the details of PM. For example, a line of work [3,8,15,16,34,57] proposes to use (software or hardware) transactions to provide (failure and thread) atomicity. Another line of work [1,4,20,25,35] advocates use of locks or synchronization-free regions [17].…”

Section: Related Workmentioning

confidence: 99%

Yashme: detecting persistency races

Gorjiara

Demsky

2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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Persistent memory (PM) or Non-Volatile Random-Access Memory (NVRAM) hardware such as Intel's Optane memory product promises to transform how programs store and manipulate information. Ensuring that persistent memory programs are crash consistent is a major challenge. We present a novel class of crash consistency bugs for persistent memory programs, which we call persistency races. Persistency races can cause non-atomic stores to be made partially persistent. Persistency races arise due to the interaction of standard compiler optimizations with persistent memory semantics.We present Yashme, the first detector for persistency races. A major challenge is that in order to detect persistency races, the execution must crash in a very narrow window between a store with a persistency race and its corresponding cache flush operation, making it challenging for naïve techniques to be effective. Yashme overcomes this challenge with a novel technique for detecting races in executions that are prefixes of the pre-crash execution. This technique enables Yashme to effectively find persistency races even if the injected crashes do not fall into that window. We have evaluated Yashme on a range of persistent memory benchmarks and have found 24 real persistency races that have never been reported before. CCS CONCEPTS• Hardware → Memory and dense storage; • Software and its engineering → Software verification and validation; Compilers.

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Clobber-NVM: log less, re-execute more

Cited by 19 publications

References 51 publications

The performance power of software combining in persistence

The performance power of software combining in persistence

Efficiently detecting concurrency bugs in persistent memory programs

Yashme: detecting persistency races

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