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Documents authored by Brown, Trevor

Document
DOI: 10.4230/LIPIcs.OPODIS.2022.7
Performance Anomalies in Concurrent Data Structure Microbenchmarks

Authors: Rosina F. Kharal and Trevor Brown

Published in: LIPIcs, Volume 253, 26th International Conference on Principles of Distributed Systems (OPODIS 2022)

Abstract
Recent decades have witnessed a surge in the development of concurrent data structures with an increasing interest in data structures implementing concurrent sets (CSets). Microbenchmarking tools are frequently utilized to evaluate and compare the performance differences across concurrent data structures. The underlying structure and design of the microbenchmarks themselves can play a hidden but influential role in performance results. However, the impact of microbenchmark design has not been well investigated. In this work, we illustrate instances where concurrent data structure performance results reported by a microbenchmark can vary 10-100x depending on the microbenchmark implementation details. We investigate factors leading to performance variance across three popular microbenchmarks and outline cases in which flawed microbenchmark design can lead to an inversion of performance results between two concurrent data structure implementations. We further derive a set of recommendations for best practices in the design and usage of concurrent data structure microbenchmarks and explore advanced features in the Setbench microbenchmark.
Cite as

Rosina F. Kharal and Trevor Brown. Performance Anomalies in Concurrent Data Structure Microbenchmarks. In 26th International Conference on Principles of Distributed Systems (OPODIS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 253, pp. 7:1-7:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{kharal_et_al:LIPIcs.OPODIS.2022.7,
  author =	{Kharal, Rosina F. and Brown, Trevor},
  title =	{{Performance Anomalies in Concurrent Data Structure Microbenchmarks}},
  booktitle =	{26th International Conference on Principles of Distributed Systems (OPODIS 2022)},
  pages =	{7:1--7:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-265-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{253},
  editor =	{Hillel, Eshcar and Palmieri, Roberto and Rivi\`{e}re, Etienne},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.OPODIS.2022.7},
  URN =		{urn:nbn:de:0030-drops-176273},
  doi =		{10.4230/LIPIcs.OPODIS.2022.7},
  annote =	{Keywords: concurrent microbenchmarks, concurrent data structures, concurrent performance evaluation, PRNGs, parallel computing}
}
Document
Brief Announcement
DOI: 10.4230/LIPIcs.DISC.2022.45
Brief Announcement: Performance Anomalies in Concurrent Data Structure Microbenchmarks

Authors: Rosina F. Kharal and Trevor Brown

Published in: LIPIcs, Volume 246, 36th International Symposium on Distributed Computing (DISC 2022)

Abstract
Recent decades have witnessed a surge in the development of concurrent data structures with an increasing interest in data structures implementing concurrent sets (CSets). Microbenchmarking tools are frequently utilized to evaluate and compare performance differences across concurrent data structures. The underlying structure and design of the microbenchmarks themselves can play a hidden but influential role in performance results. However, the impact of microbenchmark design has not been well investigated. In this work, we illustrate instances where concurrent data structure performance results reported by a microbenchmark can vary 10-100x depending on the microbenchmark implementation details. We investigate factors leading to performance variance across three popular microbenchmarks and outline cases in which flawed microbenchmark design can lead to an inversion of performance results between two concurrent data structure implementations. We further derive a prescriptive approach for best practices in the design and utilization of concurrent data structure microbenchmarks.
Cite as

Rosina F. Kharal and Trevor Brown. Brief Announcement: Performance Anomalies in Concurrent Data Structure Microbenchmarks. In 36th International Symposium on Distributed Computing (DISC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 246, pp. 45:1-45:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{kharal_et_al:LIPIcs.DISC.2022.45,
  author =	{Kharal, Rosina F. and Brown, Trevor},
  title =	{{Brief Announcement: Performance Anomalies in Concurrent Data Structure Microbenchmarks}},
  booktitle =	{36th International Symposium on Distributed Computing (DISC 2022)},
  pages =	{45:1--45:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-255-6},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{246},
  editor =	{Scheideler, Christian},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2022.45},
  URN =		{urn:nbn:de:0030-drops-172363},
  doi =		{10.4230/LIPIcs.DISC.2022.45},
  annote =	{Keywords: concurrent microbenchmarks, concurrent data structures, high performance simulations, PRNGs}
}
Document
DOI: 10.4230/LIPIcs.DISC.2017.4
Reuse, Don't Recycle: Transforming Lock-Free Algorithms That Throw Away Descriptors

Authors: Maya Arbel-Raviv and Trevor Brown

Published in: LIPIcs, Volume 91, 31st International Symposium on Distributed Computing (DISC 2017)

Abstract
In many lock-free algorithms, threads help one another, and each operation creates a descriptor that describes how other threads should help it. Allocating and reclaiming descriptors introduces significant space and time overhead. We introduce the first descriptor abstract data type (ADT), which captures the usage of descriptors by lock-free algorithms. We then develop a weak descriptor ADT which has weaker semantics, but can be implemented significantly more efficiently. We show how a large class of lock-free algorithms can be transformed to use weak descriptors, and demonstrate our technique by transforming several algorithms, including the leading k-compare-and-swap (k-CAS) algorithm. The original k-CAS algorithm allocates at least k+1 new descriptors per k-CAS. In contrast, our implementation allocates two descriptors per process, and each process simply reuses its two descriptors. Experiments on a variety of workloads show significant performance improvements over implementations that reclaim descriptors, and reductions of up to three orders of magnitude in peak memory usage.
Cite as

Maya Arbel-Raviv and Trevor Brown. Reuse, Don't Recycle: Transforming Lock-Free Algorithms That Throw Away Descriptors. In 31st International Symposium on Distributed Computing (DISC 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 91, pp. 4:1-4:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{arbelraviv_et_al:LIPIcs.DISC.2017.4,
  author =	{Arbel-Raviv, Maya and Brown, Trevor},
  title =	{{Reuse, Don't Recycle: Transforming Lock-Free Algorithms That Throw Away Descriptors}},
  booktitle =	{31st International Symposium on Distributed Computing (DISC 2017)},
  pages =	{4:1--4:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-053-8},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{91},
  editor =	{Richa, Andr\'{e}a},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2017.4},
  URN =		{urn:nbn:de:0030-drops-80092},
  doi =		{10.4230/LIPIcs.DISC.2017.4},
  annote =	{Keywords: Concurrency, data structures, lock-free, synchronization, descriptors}
}
Document
DOI: 10.4230/LIPIcs.DISC.2017.9
Cost of Concurrency in Hybrid Transactional Memory

Authors: Trevor Brown and Srivatsan Ravi

Published in: LIPIcs, Volume 91, 31st International Symposium on Distributed Computing (DISC 2017)

Abstract
State-of-the-art software transactional memory (STM) implementations achieve good performance by carefully avoiding the overhead of incremental validation (i.e., re-reading previously read data items to avoid inconsistency) while still providing progressiveness (allowing transactional aborts only due to data conflicts). Hardware transactional memory (HTM) implementations promise even better performance, but offer no progress guarantees. Thus, they must be combined with STMs, leading to hybrid TMs (HyTMs) in which hardware transactions must be instrumented (i.e., access metadata) to detect contention with software transactions. We show that, unlike in progressive STMs, software transactions in progressive HyTMs cannot avoid incremental validation. In fact, this result holds even if hardware transactions can read metadata non-speculatively. We then present opaque HyTM algorithms providing progressiveness for a subset of transactions that are optimal in terms of hardware instrumentation. We explore the concurrency vs. hardware instrumentation vs. software validation trade-offs for these algorithms. Our experiments with Intel and IBM POWER8 HTMs seem to suggest that (i) the cost of concurrency also exists in practice, (ii) it is important to implement HyTMs that provide progressiveness for a maximal set of transactions without incurring high hardware instrumentation overhead or using global contending bottlenecks and (iii) there is no easy way to derive more efficient HyTMs by taking advantage of non-speculative accesses within hardware.
Cite as

Trevor Brown and Srivatsan Ravi. Cost of Concurrency in Hybrid Transactional Memory. In 31st International Symposium on Distributed Computing (DISC 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 91, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{brown_et_al:LIPIcs.DISC.2017.9,
  author =	{Brown, Trevor and Ravi, Srivatsan},
  title =	{{Cost of Concurrency in Hybrid Transactional Memory}},
  booktitle =	{31st International Symposium on Distributed Computing (DISC 2017)},
  pages =	{9:1--9:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-053-8},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{91},
  editor =	{Richa, Andr\'{e}a},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2017.9},
  URN =		{urn:nbn:de:0030-drops-79958},
  doi =		{10.4230/LIPIcs.DISC.2017.9},
  annote =	{Keywords: Transactional memory, Lower bounds, Opacity}
}
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