While developed largely for higher density and lower power,
byte-addressable nonvolatile memory can also allow data
to persist across program runs and system crashes without
the need to flush to disk or flash. If data is to be recovered
after a crash, however, care must be taken to ensure that the
contents of memory are consistent at all times. This can be
challenging in multithreaded applications with write-back
caches. We present QSTM, a persistent word-based software
transactional memory (STM) system to address this problem.
Unlike past such systems, QSTM is nonblocking and does
not require either the modification of target data structures
or the use of a wide CAS instruction.
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Nonblocking Persistent Software Transactional Memory
Newly emerging nonvolatile alternatives to DRAM raise the possibility that applications might compute directly on long-lived data, rather than serializing them to and from a file system or database. To ensure crash consistency, such data must, like a file system or database, provide failure-atomic transactional semantics. Several persistent software transactional memory (STM) systems have been devised to provide these semantics, but only one—the OneFile system of Ramalhete et al.—is nonblocking. Nonblocking progress is desirable to avoid both performance anomalies due to process preemption or failures and deadlock due to priority inversion. Unfortunately, OneFile achieves nonblocking progress at the cost of 2× space overhead, sacrificing much of the cost and density benefit of nonvolatile memory relative to DRAM. OneFile also requires extensive and intrusive changes to data declarations, and works only on a machine with double-width compare-and-swap (CAS) or load-linked/store-conditional (LL/SC) instructions. To address these limitations, we introduce QSTM, a nonblocking persistent STM that requires neither the modification of target data structures nor the availability of a wide CAS instruction. We describe our system, give arguments for safety and liveness, and compare performance to that of the Mnemosyne and OneFile persistent STM systems. We argue that modest performance costs (within a factor of 2 of OneFile in almost all cases) are easily justified by dramatically lower space overhead and higher programmer convenience.
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- NSF-PAR ID:
- 10294977
- Date Published:
- Journal Name:
- 27th Intl. Conf. on High Performance Computing, Data, and Analytics (HiPC)
- Page Range / eLocation ID:
- 283 to 293
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/HiPC50609.2020.00042
