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Article . 2006 . Peer-reviewed
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https://doi.org/10.1109/hpca.2...
Article . 2005 . Peer-reviewed
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Unbounded Transactional Memory

Authors: C. Scott Ananian; Krste Asanovic; Bradley C. Kuszmaul; Charles E. Leiserson; Sean Lie;

Unbounded Transactional Memory

Abstract

Hardware transactional memory should support unbounded transactions: transactions of arbitrary size and duration. We describe a hardware implementation of unbounded transactional memory, called UTM, which exploits the common case for performance without sacrificing correctness on transactions whose footprint can be nearly as large as virtual memory. We performed a cycle-accurate simulation of a simplified architecture, called LTM. LTM is based on UTM but is easier to implement, because it does not change the memory subsystem outside of the processor. LTM allows nearly unbounded transactions, whose footprint is limited only by physical memory size and whose duration by the length of a timeslice. We assess UTM and LTM through microbenchmarking and by automatically converting the SPECjvm98 Java benchmarks and the Linux 2.4.19 kernel to use transactions instead of locks. We use both cycle-accurate simulation and instrumentation to understand benchmark behavior. Our studies show that the common case is small transactions that commit, even when contention is high, but that some applications contain very large transactions. For example, although 99.9% of transactions in the Linux study touch 54 cache lines or fewer, some transactions touch over 8000 cache lines. Our studies also indicate that hardware support is required, because some applications spend over half their time in critical regions. Finally, they suggest that hardware support for transactions can make Java programs run faster than when run using locks and can increase the concurrency of the Linux kernel by as much as a factor of 4 with no additional programming work.

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    252
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
252
Top 10%
Top 1%
Top 1%
bronze