high performance computing on graphics processing units: hgpu.org

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Rendering of 3D Dynamic Virtual Environments

Salvatore Catanese, Emilio Ferrara, Giacomo Fiumara, Francesco Pagano

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Tags: 3D Graphics and Realism, Computer science, DirectX, Games, OpenGL, Review, Virtual reality

March 29, 2011 by hgpu

General-purpose GPU computing: practice and experience

Bartlett S. H. (Scott) Michel

Tags: Computer science, Programming techniques, Review

March 24, 2011 by hgpu

Data Visualization and Mining using the GPU

Sudipto Guha

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Tags: Computer science, Data mining, Rendering, Review, Visualization

March 23, 2011 by hgpu

GPU-based password cracking

Marcus Bakker, Roel Van Der Jagt

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Review, Security

March 21, 2011 by hgpu

Hardware Acceleration of EDA Algorithms: GPU Architecture and the CUDA Programming Model

Kanupriya Gulati and Sunil P. Khatri

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Tags: Book, CAD, Computer science, CUDA, Electronic design automation, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, nVidia Quadro FX 5800, Review

March 18, 2011 by hgpu

Using Parallel Computing for the Display and Simulation of the Space Debris Environment

M. Mockel, C. Wiedemann, S. Flegel, J. Gelhaus, P. Vorsmann, H. Klinkrad, H. Krag

Tags: Earth and Space Sciences, OpenCL, Review, Visualization

March 18, 2011 by hgpu

Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs

Kanupriya Gulati and Sunil P. Khatri

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Tags: Book, CAD, Computer science, CUDA, Electronic design automation, FPGA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, nVidia Quadro FX 5800, Review

March 14, 2011 by hgpu

Expanding the boundaries of GPU computing

Dell Power Solutions

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, Review, Tesla M1060, Tesla M2050, Tesla M2070

March 14, 2011 by hgpu

GPU for CAD

Thomas R. Kurfess, Thomas M. Tucker, Koushik Aravalli, P. M. Meghashyam

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Tags: CAD, Computer science, nVidia, nVidia Quadro FX 3000, Review, Shaders

March 13, 2011 by hgpu

Improving the Efficiency of GPU Clusters

Bill Mcmillan

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Tags: Computer science, GPU cluster, Review

March 12, 2011 by hgpu

The GPU as a high performance computational resource

Tor Dokken, Trond R Hagen, Jon M Hjelmervik

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Tags: Computer science, Linear Algebra, Mathematical Software, Partial differential equations, PDEs, Review

March 11, 2011 by hgpu

GPGPU flow

Jens Kruger

Tags: Computer science, Review, Visualization

March 9, 2011 by hgpu

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

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

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high performance computing on graphics processing units: hgpu.org

Rendering of 3D Dynamic Virtual Environments

General-purpose GPU computing: practice and experience

Data Visualization and Mining using the GPU

GPU-based password cracking

Hardware Acceleration of EDA Algorithms: GPU Architecture and the CUDA Programming Model

Using Parallel Computing for the Display and Simulation of the Space Debris Environment

Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs

Expanding the boundaries of GPU computing

GPU for CAD

Improving the Efficiency of GPU Clusters

The GPU as a high performance computational resource

GPGPU flow

Recent source codes

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

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

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