Scalable Speculative Parallelization on Commodity Clusters

Kim, Hanjun; Raman, Arun; Liu, Feng; Lee, Jae Woo; August, David I.

doi:10.1109/micro.2010.19

Cited by 20 publications

(27 citation statements)

References 20 publications

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“…The runtime system tracks every speculative memory operation within a transaction or task (i.e., region of code executed speculatively) to determine if any atomicity violation (in TM) or dependence violation (in TLS) occurs at commit time. Proposals for TM or TLS memory systems can be divided into two classes: hardware-based approaches [21,24,23] and software-only approaches [4,6,8,9,12,13,14,17,22]. Software-only approaches can be further divided depending on whether they require cache-coherent shared memory or not.…”

Section: Spec-doall Parallelization On Clustersmentioning

confidence: 99%

“…There have been proposals for TM and TLS memory systems on clusters [4,6,8,9,12], but only Cluster-STM [4] and DSMTX [8] have demonstrated their scalability on platforms with over 100 cores. In addition, among the proposals, there is no known automatic speculative parallelization system targeting them.…”

Section: Spec-doall Parallelization On Clustersmentioning

confidence: 99%

“…As a distributed transactional memory system, the runtime validates memory speculation, and manages rollbacks in the event of misspeculation. To efficiently pass live-in values on a cluster, the runtime adopts copy-on-access [8]. Section 5 presents more details of the runtime.…”

Section: Cluster Spec-doall Runtimementioning

confidence: 99%

“…To exploit parallel hardware for misspeculation detection and recovery, the Cluster Spec-DOALL runtime offloads the task of validating speculative memory accesses to a separate process, called validator process, and keeps the committed, non-speculative memory state in the master process as in [8]. Figure 8 shows how the Cluster Spec-DOALL runtime interacts with a Spec-DOALL loop.…”

Section: The Execution Modelmentioning

confidence: 99%

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Automatic speculative DOALL for clusters

Kim

Johnson

Lee

et al. 2012

Proceedings of the Tenth International Symposium on Code Generation and Optimization

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Automatic parallelization for clusters is a promising alternative to time-consuming, error-prone manual parallelization. However, automatic parallelization is frequently limited by the imprecision of static analysis. Moreover, due to the inherent fragility of static analysis, small changes to the source code can significantly undermine performance. By replacing static analysis with speculation and profiling, automatic parallelization becomes more robust and applicable. A naïve automatic speculative parallelization does not scale for distributed memory clusters, due to the high bandwidth required to validate speculation. This work is the first automatic speculative DOALL (Spec-DOALL) parallelization system for clusters. We have implemented a prototype automatic parallelization system, called Cluster Spec-DOALL, which consists of a Spec-DOALL parallelizing compiler and a speculative runtime for clusters. Since the compiler optimizes communication patterns, and the runtime is optimized for the cases in which speculation succeeds, Cluster Spec-DOALL minimizes the communication and validation overheads of the speculative runtime. Across 8 benchmarks, Cluster Spec-DOALL achieves a geomean speedup of 43.8× on a 120-core cluster, whereas DOALL without speculation achieves only 4.5× speedup. This demonstrates that speculation makes scalable fully-automatic parallelization for clusters possible.

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Section: Spec-doall Parallelization On Clustersmentioning

confidence: 99%

Section: Spec-doall Parallelization On Clustersmentioning

confidence: 99%

Section: Cluster Spec-doall Runtimementioning

confidence: 99%

Section: The Execution Modelmentioning

confidence: 99%

See 2 more Smart Citations

Automatic speculative DOALL for clusters

Kim

Johnson

Lee

et al. 2012

Proceedings of the Tenth International Symposium on Code Generation and Optimization

Self Cite

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show abstract

“…Our work is also related to a set of results in the area of automatic speculative-parallelization in general purpose applications [20]. Here we consider the issue of fault-tolerant data replication, while those works mostly target performance and latency reduction via distributed executions on, e.g., commodity clusters.…”

Section: Introductionmentioning

confidence: 99%

SPECULA: Speculative Replication of Software Transactional Memory

Peluso

Fernandes

Romano

et al. 2012

2012 IEEE 31st Symposium on Reliable Distributed Systems

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Abstract-This paper introduces SPECULA, a novel replication protocol for Software Transactional Memory (STM) systems that seeks maximum overlap between transaction execution and replica synchronization phases via speculative processing techniques. By removing the replica synchronization phase from the critical path of execution of transactions, SPEC-ULA allows threads to speculatively pipeline the execution of both transactional and/or non-transactional code. The core of SPECULA is a multi-version concurrency control algorithm that supports speculative transaction processing while ensuring the strong consistency criteria that are desirable in non-sandboxed environments like STMs. Via an experimental study, based on a fully-fledged prototype and on both synthetic and standard STM benchmarks, we demonstrate that SPECULA can achieve speedups of up to one order of magnitude with respect to state-of-the-art non-speculative replication techniques.

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Unifying Thread-Level Speculation and Transactional Memory

Barreto

Dragojević

Ferreira

et al. 2012

Lecture Notes in Computer Science

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The motivation of this work is to ask whether Transactional Memory (TM) and Thread-Level Speculation (TLS), two prominent concurrency paradigms usually considered separately, can be combined into a hybrid approach that extracts untapped parallelism and speed-up from common programs. We show that the answer is positive by describing an algorithm, called TLSTM, that leverages an existing TM with TLS capabilities. We also show that our approach is able to achieve up to a 48% increase in throughput over the base TM, on read dominated workloads of long transactions in a multi-threaded application, among other results.

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Scalable Speculative Parallelization on Commodity Clusters

Cited by 20 publications

References 20 publications

Automatic speculative DOALL for clusters

Automatic speculative DOALL for clusters

SPECULA: Speculative Replication of Software Transactional Memory

Unifying Thread-Level Speculation and Transactional Memory

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