high performance computing on graphics processing units: hgpu.org

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Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Antonio Wendellde O. Rodrigues, Vincent Aranega, Anne Etien, Frederic Guyomarc'h, Jean-Luc Dekeyser

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Tags: Algorithms, Computer science, nVidia, OpenCL, Performance, Programming techniques, Tesla S1070

October 18, 2011 by hgpu

Evaluating the Performance and Portability of OpenCL

Jarno van der Sanden

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, OpenCL, Performance, Thesis

October 18, 2011 by hgpu

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Jose M. Dominguez, Alejandro J.C. Crespo, Moncho Gomez-Gesteira

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Tags: Computational Engineering, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, OpenMP, Optimization, Performance, Tesla C1060

October 18, 2011 by hgpu

Fast Implementation of DGEMM on Fermi GPU

Guangming Tan, Linchuan Li, Sean Triechle, Everett Phillips, Yungang Bao, Ninghui Sun

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Optimization, Performance, Tesla C2050

October 17, 2011 by hgpu

Dynamic Fine-Grain Scheduling of Pipeline Parallelism

Daniel Sanchez, David Lo, Richard M. Yoo, Jeremy Sugerman, Christos Kozyrakis

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques

October 17, 2011 by hgpu

GPU-to-CPU callbacks

Jeff A. Stuart, Michael Cox, John D. Owens

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques

October 16, 2011 by hgpu

Data Layout Pruning on GPU

Xinbiao Gan, Zhiying Wang, Li Shen, Qi Zhu

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Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 280, Performance

October 16, 2011 by hgpu

Skeleton Programming for Heterogeneous GPU-based Systems

Usman Dastgeer

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla C1060, Thesis

October 16, 2011 by hgpu

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Naoya Maruyama, Tatsuo Nomura, Kento Sato, Satoshi Matsuoka

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Tags: Computer science, CUDA, MPI, nVidia, Optimization, Package, Performance, Programming Languages, Programming techniques, Tesla M2050

October 15, 2011 by hgpu

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Shuai Che, Jeremy W. Sheaffer, Kevin Skadron

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Optimization, Performance

October 15, 2011 by hgpu

GPU fluids in production: a compiler approach to parallelism

Dan Bailey, Ian Masters, Matt Warner

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Tags: Code generation, Compilers, Computer science, Image processing, nVidia, Performance, Presentation, PTX, Tesla C2050

October 15, 2011 by hgpu

Accelerating code on multi-cores with FastFlow

Marco Aldinucci, Marco Danelutto, Peter Kilpatrick, Massimiliano Meneghin, Massimo Torquati

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Tags: Computer science, Memory, Package, Performance, Programming techniques

October 15, 2011 by hgpu

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

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high performance computing on graphics processing units: hgpu.org

Enabling Traceability in an MDE Approach to Improve Performance of GPU Applications

Evaluating the Performance and Portability of OpenCL

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Fast Implementation of DGEMM on Fermi GPU

Dynamic Fine-Grain Scheduling of Pipeline Parallelism

GPU-to-CPU callbacks

Data Layout Pruning on GPU

Skeleton Programming for Heterogeneous GPU-based Systems

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

GPU fluids in production: a compiler approach to parallelism

Accelerating code on multi-cores with FastFlow

Recent source codes

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

TRUST: a thermalhydraulic software package for CFD simulations

Modular: The Modular Platform (includes MAX & Mojo)

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

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