Image de couverture de livre

Machine Learning-driven Autotuning of Graphics Processing Unit Accelerated Computational Fluid Dynamics for Enhanced Performance

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Xue, Weicheng, Roy, Christohper John
Format:	Preprint
Publié:	2023
Sujets:	Performance Computational Physics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Characterizing Machine Learning Force Fields as Emerging Molecular Dynamics Workloads on Graphics Processing Units
par: De Alwis, Udari, et autres
Publié: (2026)

Integrating ytopt and libEnsemble to Autotune OpenMC
par: Wu, Xingfu, et autres
Publié: (2024)

Portable High-Performance Kernel Generation for a Computational Fluid Dynamics Code with DaCe
par: Andersson, Måns I., et autres
Publié: (2025)

Accelerating Machine Learning Queries with Linear Algebra Query Processing
par: Sun, Wenbo, et autres
Publié: (2023)

Understanding the Impact of Synchronous, Asynchronous, and Hybrid In-Situ Techniques in Computational Fluid Dynamics Applications
par: Ju, Yi, et autres
Publié: (2024)

HPC Application Parameter Autotuning on Edge Devices: A Bandit Learning Approach
par: Hossain, Abrar, et autres
Publié: (2025)

Optimizing Near Field Computation in the MLFMA Algorithm with Data Redundancy and Performance Modeling on a Single GPU
par: Sadeghi, Morteza, et autres
Publié: (2024)

SProBench: Stream Processing Benchmark for High Performance Computing Infrastructure
par: Kulkarni, Apurv Deepak, et autres
Publié: (2025)

Enhanced Scalability in Assessing Quantum Integer Factorization Performance
par: Lee, Junseo
Publié: (2023)

An Autotuning-based Optimization Framework for Mixed-kernel SVM Classifications in Smart Pixel Datasets and Heterojunction Transistors
par: Wu, Xingfu, et autres
Publié: (2024)

A Precision Emulation Approach to the GPU Acceleration of Ab Initio Electronic Structure Calculations
par: Liu, Hang, et autres
Publié: (2026)

Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception
par: Odema, Mohanad, et autres
Publié: (2024)

Accelerating Particle-in-Cell Monte Carlo Simulations with MPI, OpenMP/OpenACC and Asynchronous Multi-GPU Programming
par: Williams, Jeremy J., et autres
Publié: (2024)

A Machine Learning accelerated geophysical fluid solver
par: Bai, Yang
Publié: (2026)

Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms
par: Lin, Zhongyi, et autres
Publié: (2024)

Accelerating the Tesseract Decoder for Quantum Error Correction
par: Grbic, Dragana, et autres
Publié: (2026)

SLO-Guard: Crash-Aware, Budget-Consistent Autotuning for SLO-Constrained LLM Serving
par: Lysenstøen, Christian
Publié: (2026)

Non-Asymptotic Performance Analysis of DOA Estimation Based on Real-Valued Root-MUSIC
par: Liu, Junyang, et autres
Publié: (2025)

TINA: Acceleration of Non-NN Signal Processing Algorithms Using NN Accelerators
par: Boerkamp, Christiaan, et autres
Publié: (2024)

Advanced Scheduling Strategies for Distributed Quantum Computing Jobs
par: Ni, Gongyu, et autres
Publié: (2026)

GPU-Accelerated Parallel Selected Inversion for Structured Matrices Using sTiles
par: Fattah, Esmail Abdul, et autres
Publié: (2025)

A Data-driven ML Approach for Maximizing Performance in LLM-Adapter Serving
par: Agullo, Ferran, et autres
Publié: (2025)

Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems
par: Williams, Jeremy J., et autres
Publié: (2026)

Characterizing the Performance of the Implicit Massively Parallel Particle-in-Cell iPIC3D Code
par: Williams, Jeremy J., et autres
Publié: (2024)

Solving Combinatorial Optimization Problems on a Photonic Quantum Computer
par: Slysz, Mateusz, et autres
Publié: (2024)

Performance of Confidential Computing GPUs
par: Ibarra, Antonio Martínez, et autres
Publié: (2025)

Scalable Systems and Software Architectures for High-Performance Computing on cloud platforms
par: Ramesh, Risshab Srinivas
Publié: (2024)

Scheduling in Quantum Satellite Networks: Fairness and Performance Optimization
par: Dikshit, Ashutosh Jayant, et autres
Publié: (2025)

Cost-Performance Evaluation of General Compute Instances: AWS, Azure, GCP, and OCI
par: Tharwani, Jay, et autres
Publié: (2024)

Integrating High Performance In-Memory Data Streaming and In-Situ Visualization in Hybrid MPI+OpenMP PIC MC Simulations Towards Exascale
par: Williams, Jeremy J., et autres
Publié: (2025)

Performance Characterization of Containers in Edge Computing
par: Gupta, Ragini, et autres
Publié: (2025)

Phantora: Maximizing Code Reuse in Simulation-based Machine Learning System Performance Estimation
par: Qin, Jianxing, et autres
Publié: (2025)

Performance metrics for the continuous distribution of entanglement in multi-user quantum networks
par: Iñesta, Álvaro G., et autres
Publié: (2023)

Enhancing Traffic Sign Recognition On The Performance Based On Yolov8
par: Ibrahim, Baba, et autres
Publié: (2025)

Performance Optimization in Stream Processing Systems: Experiment-Driven Configuration Tuning for Kafka Streams
par: Chen, David, et autres
Publié: (2026)

Efficient Transpilation of OpenQASM 3.0 Dynamic Circuits to CUDA-Q: Performance and Expressiveness Advantages
par: Kulkarni, Vinooth, et autres
Publié: (2026)

Deciphering boundary layer dynamics in high-Rayleigh-number convection using 3360 GPUs and a high-scaling in-situ workflow
par: Bode, Mathis, et autres
Publié: (2025)

Towards Run Time Estimation of the Gaussian Chemistry Code for SEAGrid Science Gateway
par: Beltre, Angel, et autres
Publié: (2019)

nekCRF: A next generation high-order reactive low Mach flow solver for direct numerical simulations
par: Kerkemeier, Stefan, et autres
Publié: (2024)

An Analysis of Performance Bottlenecks in MRI Pre-Processing
par: Dugré, Mathieu, et autres
Publié: (2024)