Academic Journal

GPU Simulation Acceleration via Parallelization

Bibliographic Details
Title: GPU Simulation Acceleration via Parallelization
Authors: Huerta Gañán, Rodrigo, González Colás, Antonio María
Source: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
2025 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
Publisher Information: IEEE, 2025.
Publication Year: 2025
Subject Terms: Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors, GPGPU, GPU, Parallelization, OpenMP, GPGPU-Sim, Microarchitecture, Accel-sim, Simulation
Description: —Simulating modern GPU architectures with increased core counts and recent workloads can be challenging, even on powerful computing platforms. In this paper, we present a simple approach to parallelize Accel-sim with minimal code changes using OpenMP. In addition, we introduce PaSSMA, a novel technique to optimize the OpenMP for-loop scheduler performance in the different simulated workloads. Moreover, our parallelization technique is deterministic, so the simulator provides exactly the same results for single-threaded and multithreaded simulations. When we run the simulator with 16 CPU cores, we achieve an average speed-up of 6.4x and reach 10x in some workloads.
This work has been supported by the CoCoUnit ERC Advanced Grant of the EU’s Horizon 2020 program (grant No 833057), the Spanish State Research Agency (MCIN/AEI) under grant PID2020-113172RB-I00, the Catalan Agency for University and Research (AGAUR) under grant 2021SGR00383, and the ICREA Academia program
Document Type: Article
Conference object
File Description: application/pdf
DOI: 10.1109/ispass64960.2025.00054
Access URL: https://hdl.handle.net/2117/440535
https://doi.org/10.1109/ispass64960.2025.00054
Rights: STM Policy #29
Accession Number: edsair.doi.dedup.....66abf0d4d05d216dc3a621a9f4f41b3d
Database: OpenAIRE
Description
DOI:10.1109/ispass64960.2025.00054