high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Dynamic detection of uniform and affine vectors in GPGPU computations

Sylvain Collange, David Defour, Yao Zhang

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Tags: Algorithms, Computer science, CUDA, Hardware Architecture, nVidia, Optimization, Tesla

April 19, 2011 by hgpu

Linear optimization on modern GPUs

Daniele G. Spampinato, Anne C. Elster

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Tags: CUDA, Finance, Matrix multiplication, nVidia, nVidia GeForce GTX 280, Optimization

April 18, 2011 by hgpu

Accelerating Particle Swarm Algorithm with GPGPU

M. Cadenas-Montes, M.A. Vega-Rodriguez, J.J. Rodriguez-Vazquez, A. Gomez-Iglesias

Tags: Algorithms, Computer science, Evolutionary Computations, Optimization

April 16, 2011 by hgpu

Speeding up K-Means Algorithm by GPUs

You Li, Kaiyong Zhao, Xiaowen Chu, Jiming Liu

Tags: Algorithms, Computer science, Matrix multiplication, Optimization

April 13, 2011 by hgpu

NQueens on CUDA: Optimization Issues

Frank Feinbube, Bernhard Rabe, Martin von Lowis, Andreas Polze

Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, Optimization

April 13, 2011 by hgpu

Implementation and optimization of image processing algorithms on handheld GPU

Nitin Singhal, In Kyu Park, Sungdae Cho

Tags: Algorithms, Image processing, OpenGL, Optimization, Rendering

April 12, 2011 by hgpu

Power analysis and optimizations for GPU architecture using a power simulator

Guibin Wang

Tags: Computer science, Energy-efficient computing, Optimization

April 12, 2011 by hgpu

CUDA Memory Optimizations for Large Data-Structures in the Gravit Simulator

Jakob Siegel, Juergen Ributzka, Xiaoming Li

Tags: Computer science, CUDA, Gravitation, Memory model, N-body simulation, nVidia, Optimization

April 12, 2011 by hgpu

Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluate CUDA Optimizations

Ruyman Reyes, Francisco de Sande

Tags: Computer science, CUDA, nVidia, Optimization

April 8, 2011 by hgpu

Program Optimization of Stencil Based Application on the GPU-Accelerated System

Guibin Wang, Xuejun Yang, Ying Zhang, Tao Tang, XuDong Fang

Tags: Computer science, Optimization

April 7, 2011 by hgpu

Using GPU to Accelerate Cache Simulation

Wan Han, Gao Xiaopeng, Wang Zhiqiang, Li Yi

Tags: Algorithms, Computer science, CUDA, Memory, nVidia, Optimization

April 7, 2011 by hgpu

Toward Harnessing DOACROSS Parallelism for Multi-GPGPUs

Peng Di, Qing Wan, Xuemeng Zhang, Hui Wu, Jingling Xue

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Tags: Computer science, nVidia, Optimization, Tesla C1060

April 6, 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

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high performance computing on graphics processing units: hgpu.org

Dynamic detection of uniform and affine vectors in GPGPU computations

Linear optimization on modern GPUs

Accelerating Particle Swarm Algorithm with GPGPU

Speeding up K-Means Algorithm by GPUs

NQueens on CUDA: Optimization Issues

Implementation and optimization of image processing algorithms on handheld GPU

Power analysis and optimizations for GPU architecture using a power simulator

CUDA Memory Optimizations for Large Data-Structures in the Gravit Simulator

Optimize or Wait? Using llc Fast-Prototyping Tool to Evaluate CUDA Optimizations

Program Optimization of Stencil Based Application on the GPU-Accelerated System

Using GPU to Accelerate Cache Simulation

Toward Harnessing DOACROSS Parallelism for Multi-GPGPUs

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

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