Article

Active memory operations

Authors:

John B. Carter,

Ali Ibrahim, and

Michael A. ParkerAuthors Info & Claims

ICS '07: Proceedings of the 21st annual international conference on Supercomputing

June 2007

Pages 232 - 241

https://doi.org/10.1145/1274971.1275004

Published: 17 June 2007 Publication History

Abstract

The performance of modern microprocessors is increasingly limited by their inability to hide main memory latency. The problem is worse in large-scale shared memory systems, where remote memory latencies are hundreds, and soon thousands, of processor cycles. To mitigate this problem, we propose the use of Active Memory Operations (AMOs), in which select operations can be sent to and executed on the home memory controller of data. AMOs can eliminate significant number of coherence messages, minimize intranode and internode memory traffic, and create opportunities for parallelism. Our implementation of AMOs is cache-coherent and requires no changes to the processor core or DRAM chips.

In this paper we present architectural and programming models for AMOs, and compare its performance to that of several other memory architectures on a variety of scientific and commercial benchmarks. Through simulation we show that AMOs offer dramatic performance improvements for an important set of data-intensive operations, e.g., up to 50X faster barriers, 12X faster spinlocks, 8.5X-15X faster stream/array operations, and 3X faster database queries. Based on a standard cell implementation, we predict that the circuitry required to support AMOs is less than 1% of the typical chip area of a high performance microprocessor.

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Cited By

Soria-Pardos VArmejach AMück TSuárez-Gracia DJoao JRico AMoretó MSolihin YHeinrich M(2023)DynAMO: Improving Parallelism Through Dynamic Placement of Atomic Memory OperationsProceedings of the 50th Annual International Symposium on Computer Architecture10.1145/3579371.3589065(1-13)Online publication date: 17-Jun-2023
https://dl.acm.org/doi/10.1145/3579371.3589065
Rai SSivasubramaniam AKumar ARengasamy PNarayanan VAkel AEilert SPalesi MTumeo AGoumas GAlmudever C(2021)Design space for scaling-in general purpose computing within the DDR DRAM hierarchy for map-reduce workloadsProceedings of the 18th ACM International Conference on Computing Frontiers10.1145/3457388.3458661(113-123)Online publication date: 11-May-2021
https://dl.acm.org/doi/10.1145/3457388.3458661
Lee JKim H(2018)StaleLearn: Learning Acceleration with Asynchronous Synchronization Between Model Replicas on PIMIEEE Transactions on Computers10.1109/TC.2017.278023767:6(861-873)Online publication date: 1-Jun-2018
https://doi.org/10.1109/TC.2017.2780237
Show More Cited By

Index Terms

Active memory operations
1. Computer systems organization
  1. Architectures
    1. Parallel architectures
      1. Multiple instruction, multiple data
2. Hardware
  1. Robustness

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cover image ACM Conferences

ICS '07: Proceedings of the 21st annual international conference on Supercomputing

June 2007

315 pages

ISBN:9781595937681

DOI:10.1145/1274971

General Chair:
Burton Smith
Microsoft

Copyright © 2007 ACM.

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Published: 17 June 2007

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ICS07: International Conference on Supercomputing

June 17 - 21, 2007

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Overall Acceptance Rate 629 of 2,180 submissions, 29%

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Cited By

Soria-Pardos VArmejach AMück TSuárez-Gracia DJoao JRico AMoretó MSolihin YHeinrich M(2023)DynAMO: Improving Parallelism Through Dynamic Placement of Atomic Memory OperationsProceedings of the 50th Annual International Symposium on Computer Architecture10.1145/3579371.3589065(1-13)Online publication date: 17-Jun-2023
https://dl.acm.org/doi/10.1145/3579371.3589065
Rai SSivasubramaniam AKumar ARengasamy PNarayanan VAkel AEilert SPalesi MTumeo AGoumas GAlmudever C(2021)Design space for scaling-in general purpose computing within the DDR DRAM hierarchy for map-reduce workloadsProceedings of the 18th ACM International Conference on Computing Frontiers10.1145/3457388.3458661(113-123)Online publication date: 11-May-2021
https://dl.acm.org/doi/10.1145/3457388.3458661
Lee JKim H(2018)StaleLearn: Learning Acceleration with Asynchronous Synchronization Between Model Replicas on PIMIEEE Transactions on Computers10.1109/TC.2017.278023767:6(861-873)Online publication date: 1-Jun-2018
https://doi.org/10.1109/TC.2017.2780237
Castillo EAlvarez LMoreto MCasas MVallejo EBosque JBeivide RValero M(2018)Architectural Support for Task Dependence Management with Flexible Software Scheduling2018 IEEE International Symposium on High Performance Computer Architecture (HPCA)10.1109/HPCA.2018.00033(283-295)Online publication date: Feb-2018
https://doi.org/10.1109/HPCA.2018.00033
Lee JChung JAhn JChoi K(2017)Excavating the Hidden Parallelism Inside DRAM Architectures With Buffered ComparesIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2017.265572225:6(1793-1806)Online publication date: Jun-2017
https://doi.org/10.1109/TVLSI.2017.2655722
Shun J(2017)Shared-Memory Parallelism Can Be Simple, Fast, and ScalableundefinedOnline publication date: 9-Jun-2017
Lee JAhn JChoi KFanucci LTeich J(2016)Buffered comparesProceedings of the 2016 Conference on Design, Automation & Test in Europe10.5555/2971808.2972099(1243-1248)Online publication date: 14-Mar-2016
https://dl.acm.org/doi/10.5555/2971808.2972099
Siegl PBuchty RBerekovic MJacob B(2016)Data-Centric Computing FrontiersProceedings of the Second International Symposium on Memory Systems10.1145/2989081.2989087(295-308)Online publication date: 3-Oct-2016
https://dl.acm.org/doi/10.1145/2989081.2989087
Hong BKim GAhn JKwon YKim HKim JZaks AMendelson BRauchwerger LHwu W(2016)Accelerating Linked-list Traversal Through Near-Data ProcessingProceedings of the 2016 International Conference on Parallel Architectures and Compilation10.1145/2967938.2967958(113-124)Online publication date: 11-Sep-2016
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Panda REckert YJayasena NKayiran OBoyer MJohn L(2016)Prefetching Techniques for Near-memory Throughput ProcessorsProceedings of the 2016 International Conference on Supercomputing10.1145/2925426.2926282(1-14)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1145/2925426.2926282
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