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Using colored petri nets for GPGPU performance modeling

Published: 16 May 2016 Publication History

Abstract

Performance analysis and modeling of applications running on GPUs is still a challenge for most designers and developers. State-of-the-art solutions are dominated by two classic approaches: statistical models that require a lot of training and profiling on existing hardware, and analytical models that require in-depth knowledge of the hardware platform and significant calibration. Both these classes separate the application from the hardware and attempt a high-level combination of the two models for performance prediction. In this work, we propose an orthogonal approach, based on high-level simulation. Specifically, we use Colored Petri Nets (CPN) to model both the hardware and the application. Using this model, the execution of the application is a simulation of the CPN model using warps as tokens. Our prototype implementation of this modeling approach demonstrates promising results on a few case studies on two different GPU architectures: both reasonably accurate predictions and detailed execution information are obtained. We conclude that CPN-based GPU performance modeling is an elegant solution for systematic performance prediction, and we focus further on optimizing the models to improve the execution time of the symbolic simulation.

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Cited By

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  • (2023)Modeling of GPGPU architectures for performance analysis of CUDA programs2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security (QRS)10.1109/QRS60937.2023.00079(761-771)Online publication date: 22-Oct-2023
  • (2022)Case of Discrete-Event Simulation of the Simple Sensor Node with CPN Tools2022 International Siberian Conference on Control and Communications (SIBCON)10.1109/SIBCON56144.2022.10002956(1-9)Online publication date: 17-Nov-2022
  • (2020)High-level hardware feature extraction for GPU performance prediction of stencilsProceedings of the 13th Annual Workshop on General Purpose Processing using Graphics Processing Unit10.1145/3366428.3380769(21-30)Online publication date: 23-Feb-2020
  • Show More Cited By

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Published In

cover image ACM Conferences
CF '16: Proceedings of the ACM International Conference on Computing Frontiers
May 2016
487 pages
ISBN:9781450341288
DOI:10.1145/2903150
  • General Chairs:
  • Gianluca Palermo,
  • John Feo,
  • Program Chairs:
  • Antonino Tumeo,
  • Hubertus Franke
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 16 May 2016

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Author Tags

  1. GPU architectures
  2. colored petri nets
  3. performance modeling and analysis
  4. performance prediction

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CF'16
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CF'16: Computing Frontiers Conference
May 16 - 19, 2016
Como, Italy

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CF '16 Paper Acceptance Rate 30 of 94 submissions, 32%;
Overall Acceptance Rate 273 of 785 submissions, 35%

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Cited By

View all
  • (2023)Modeling of GPGPU architectures for performance analysis of CUDA programs2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security (QRS)10.1109/QRS60937.2023.00079(761-771)Online publication date: 22-Oct-2023
  • (2022)Case of Discrete-Event Simulation of the Simple Sensor Node with CPN Tools2022 International Siberian Conference on Control and Communications (SIBCON)10.1109/SIBCON56144.2022.10002956(1-9)Online publication date: 17-Nov-2022
  • (2020)High-level hardware feature extraction for GPU performance prediction of stencilsProceedings of the 13th Annual Workshop on General Purpose Processing using Graphics Processing Unit10.1145/3366428.3380769(21-30)Online publication date: 23-Feb-2020
  • (2018)GPU Computations and Memory Access Model Based on Petri NetsTransactions on Petri Nets and Other Models of Concurrency XIII10.1007/978-3-662-58381-4_7(136-157)Online publication date: 21-Nov-2018

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