high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Improving Performance of OpenCL on CPUs

Ralf Karrenberg, Sebastian Hack

View

Download (PDF)

Tags: Code generation, Computer science, Data parallelism, OpenCL, Performance

March 27, 2012 by hgpu

OpenMPC: Extended OpenMP for Efficient Programming and Tuning on GPUs

Seyong Lee, Rudolf Eigenmann

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, OpenMP, Performance, Programming techniques

March 26, 2012 by hgpu

Impact of asynchronism on GPU accelerated parallel iterative computations

Sylvain Contassot-Vivier, Thomas Jost, Stephane Vialle

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, Partial differential equations, PDEs, Performance

March 22, 2012 by hgpu

Accelerating Sparse Matrix Vector Multiplication on Many-Core GPUs

Weizhi Xu, Zhiyong Liu, Dongrui Fan, Shuai Jiao, Xiaochun Ye, Fenglong Song, Chenggang Yan

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 295, Performance, Sparse matrix

March 21, 2012 by hgpu

Generating optimal CUDA sparse matrix-vector product implementations for evolving GPU hardware

Ahmed H. El Zein, Alistair P. Rendell

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 295, Performance, Sparse matrix, Tesla S2050

March 19, 2012 by hgpu

Towards user transparent parallel multimedia computing on GPU-clusters

Ben van Werkhoven, Jason Maassen, Frank J. Seinstra

View

Download (PDF)

Tags: Computer science, CUDA, GPU cluster, nVidia, Performance, Tesla M1060

March 18, 2012 by hgpu

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

John Jenkins, Pavan Balaji, James Dinan, Nagiza F. Samatova, Rajeev Thakur

View

Download (PDF)

Tags: Computer science, CUDA, MPI, nVidia, Performance, Programming Languages, Programming techniques, Tesla C2050

March 18, 2012 by hgpu

Usable assembly language for GPUs: a success story

Daniel J. Bernstein, Hsieh-Chung Chen, Chen-Mou Cheng, Tanja Lange, Ruben Niederhagen, Peter Schwabe, Bo-Yin Yang

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Performance, PTX, Security

March 18, 2012 by hgpu

Performance analysis and optimization of the OP2 framework on many-core architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, CUDA, Fluid dynamics, nVidia, OpenMP, Optimization, Package, Performance, Tesla C2050

March 15, 2012 by hgpu

Analyzing CUDA’s Compiler through the Visualization of Decoded GPU Binaries

Cedric Nugteren, Bart Mesman, Henk Corporaal

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, Performance, Visualization

March 13, 2012 by hgpu

Better speedups using simpler parallel programming for graph connectivity and biconnectivity

James A. Edwards, Uzi Vishkin

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Performance, Programming techniques

March 11, 2012 by hgpu

NUMA Data-Access Bandwidth Characterization and Modeling

Ryan Karl Braithwaite

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C2050, Tesla M2050, Thesis

March 11, 2012 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

* * *

high performance computing on graphics processing units: hgpu.org

Improving Performance of OpenCL on CPUs

OpenMPC: Extended OpenMP for Efficient Programming and Tuning on GPUs

Impact of asynchronism on GPU accelerated parallel iterative computations

Accelerating Sparse Matrix Vector Multiplication on Many-Core GPUs

Generating optimal CUDA sparse matrix-vector product implementations for evolving GPU hardware

Towards user transparent parallel multimedia computing on GPU-clusters

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

Usable assembly language for GPUs: a success story

Performance analysis and optimization of the OP2 framework on many-core architectures

Analyzing CUDA’s Compiler through the Visualization of Decoded GPU Binaries

Better speedups using simpler parallel programming for graph connectivity and biconnectivity

NUMA Data-Access Bandwidth Characterization and Modeling

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

Most viewed papers (last 30 days)