high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

A parallelization cost model for GPU

Zhang Dan, Zhao Rongcai, Han Lin, Wang Tao, Qu Jin

Tags: Computer science, Optimization, Performance

March 27, 2011 by hgpu

Modeling GPU-CPU Workloads and Systems

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili

View

Download (PDF)

Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce 8600 GS, nVidia GeForce GTX 280, Performance, Task scheduling, Tesla C1060

March 23, 2011 by hgpu

Aspects of GPU for general purpose high performance computing

Takayuki Aoki, Shoichi Hirasawa, Akira Nukada, Hiroki Honda, Satoshi Matsuoka

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques, Task scheduling

March 23, 2011 by hgpu

Improving accuracy for matrix multiplications on GPUs

Matthew Badin, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Performance

March 22, 2011 by hgpu

Performance comparison of FPGA, GPU and CPU in image processing

Shuichi Asano, Tsutomu Maruyama, Yoshiki Yamaguchi

Tags: Filtering, FPGA, Image processing, Performance

March 21, 2011 by hgpu

An approach for the effective utilization of GP-GPUs in parallel combined simulation

David W. Bauer, Matthew McMahon, Ernest H. Page

Tags: Computer science, Heterogeneous systems, Partial differential equations, PDEs, Performance

March 21, 2011 by hgpu

Joint Forces: From Multithreaded Programming to GPU Computing

Frank Feinbube, Peter Troger, Andreas Polze

Tags: Computer science, Optimization, Performance

March 20, 2011 by hgpu

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

J. Myre, S. D. C. Walsh, D. Lilja, M. O. Saar

Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, OpenMP, Performance

March 17, 2011 by hgpu

Implementing the Himeno benchmark with CUDA on GPU clusters

Everett H. Phillips, Massimiliano Fatica

Tags: Benchmarking, Computer science, CUDA, GPU cluster, nVidia, Performance, Tesla C1060

March 16, 2011 by hgpu

Patterns of Inefficient Performance Behavior in GPU Applications

Dominic Eschweiler, Daniel Becker, Felix Wolf

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla T10

March 16, 2011 by hgpu

General-purpose molecular dynamics simulations on GPU-based clusters

Christian R. Trott, Lars Winterfeld, Paul S. Crozier

View

Download (PDF)

Source codes

Tags: Computational Physics, Condensed matter, CUDA, GPU cluster, Materials Science, Molecular dynamics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Performance, Physics, Tesla C1060, Tesla S1070

March 8, 2011 by hgpu

Non-blocking programming on multi-core graphics processors: (extended asbtract)

Phuong Hoai Ha, Philippas Tsigas, Otto J. Anshus

View

Download (PDF)

Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques

March 7, 2011 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

A parallelization cost model for GPU

Modeling GPU-CPU Workloads and Systems

Aspects of GPU for general purpose high performance computing

Improving accuracy for matrix multiplications on GPUs

Performance comparison of FPGA, GPU and CPU in image processing

An approach for the effective utilization of GP-GPUs in parallel combined simulation

Joint Forces: From Multithreaded Programming to GPU Computing

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

Implementing the Himeno benchmark with CUDA on GPU clusters

Patterns of Inefficient Performance Behavior in GPU Applications

General-purpose molecular dynamics simulations on GPU-based clusters

Non-blocking programming on multi-core graphics processors: (extended asbtract)

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Most viewed papers (last 30 days)