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Processing data streams with hard real-time constraints on heterogeneous systems

Published: 31 May 2011 Publication History

Abstract

Data stream processing applications such as stock exchange data analysis, VoIP streaming, and sensor data processing pose two conflicting challenges: short per-stream latency -- to satisfy the milliseconds-long, hard real-time constraints of each stream, and high throughput -- to enable efficient processing of as many streams as possible. High-throughput programmable accelerators such as modern GPUs hold high potential to speed up the computations. However, their use for hard real-time stream processing is complicated by slow communications with CPUs, variable throughput changing non-linearly with the input size, and weak consistency of their local memory with respect to CPU accesses. Furthermore, their coarse grain hardware scheduler renders them unsuitable for unbalanced multi-stream workloads.
We present a general, efficient and practical algorithm for hard real-time stream scheduling in heterogeneous systems. The algorithm assigns incoming streams of different rates and deadlines to CPUs and accelerators. By employing novel stream schedulability criteria for accelerators, the algorithm finds the assignment which simultaneously satisfies the aggregate throughput requirements of all the streams and the deadline constraint of each stream alone.
Using the AES-CBC encryption kernel, we experimented extensively on thousands of streams with realistic rate and deadline distributions. Our framework outperformed the alternative methods by allowing 50% more streams to be processed with provably deadline-compliant execution even for deadlines as short as tens milliseconds. Overall, the combined GPU-CPU execution allows for up to 4-fold throughput increase over highly-optimized multi-threaded CPU-only implementations.

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Cited By

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  • (2022)iGPU-Accelerated Pattern Matching on Event StreamsProceedings of the 18th International Workshop on Data Management on New Hardware10.1145/3533737.3535099(1-7)Online publication date: 12-Jun-2022
  • (2021)Fine-Grained Multi-Query Stream Processing on Integrated ArchitecturesIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2021.306640732:9(2303-2320)Online publication date: 1-Sep-2021
  • (2021)Deadline-Aware Offloading for High-Throughput Accelerators2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA51647.2021.00048(479-492)Online publication date: Feb-2021
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    cover image ACM Conferences
    ICS '11: Proceedings of the international conference on Supercomputing
    May 2011
    398 pages
    ISBN:9781450301022
    DOI:10.1145/1995896
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    Publication History

    Published: 31 May 2011

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    Author Tags

    1. accelerator
    2. batch processing
    3. data streams
    4. gpu
    5. hard real-time
    6. scheduling

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    ICS '11
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    ICS '11: International Conference on Supercomputing
    May 31 - June 4, 2011
    Arizona, Tucson, USA

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

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    Cited By

    View all
    • (2022)iGPU-Accelerated Pattern Matching on Event StreamsProceedings of the 18th International Workshop on Data Management on New Hardware10.1145/3533737.3535099(1-7)Online publication date: 12-Jun-2022
    • (2021)Fine-Grained Multi-Query Stream Processing on Integrated ArchitecturesIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2021.306640732:9(2303-2320)Online publication date: 1-Sep-2021
    • (2021)Deadline-Aware Offloading for High-Throughput Accelerators2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA51647.2021.00048(479-492)Online publication date: Feb-2021
    • (2020)FineStreamProceedings of the 2020 USENIX Conference on Usenix Annual Technical Conference10.5555/3489146.3489189(633-647)Online publication date: 15-Jul-2020
    • (2020)Hardware-Conscious Stream ProcessingACM SIGMOD Record10.1145/3385658.338566248:4(18-29)Online publication date: 25-Feb-2020
    • (2019)Event Stream Processing on Heterogeneous System ArchitectureProceedings of the 15th International Workshop on Data Management on New Hardware10.1145/3329785.3329933(1-10)Online publication date: 1-Jul-2019
    • (2019)A Comprehensive Survey on Parallelization and Elasticity in Stream ProcessingACM Computing Surveys10.1145/330384952:2(1-37)Online publication date: 30-Apr-2019
    • (2018)JugglerACM SIGPLAN Notices10.1145/3200691.317849253:1(54-67)Online publication date: 10-Feb-2018
    • (2018)JugglerProceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming10.1145/3178487.3178492(54-67)Online publication date: 10-Feb-2018
    • (2018)Recent Advancements in Event ProcessingACM Computing Surveys10.1145/317043251:2(1-36)Online publication date: 13-Feb-2018
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