high performance computing on graphics processing units: hgpu.org

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GPU-based simulation of brain neuron models

H. A. Du Nguyen

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Tags: CUDA, Neural networks, Neuroscience, nVidia, nVidia GeForce GT 640, Review, Tesla C2075, Thesis

September 7, 2013 by hgpu

A Survey on GPU System Considering its Performance on Different Applications

D. Londhe, P. Barapatre, N. Gholap,S. Das

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Tags: CUDA, nVidia, Performance, Review

September 6, 2013 by hgpu

Bitcoin and The Age of Bespoke Silicon

Michael Bedford Taylor

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Tags: ASIC, ATI, Finance, FPGA, nVidia, OpenCL, Performance, Review

August 31, 2013 by hgpu

GPU Computing in Economics

Eric M. Aldrich

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Tags: CUDA, Finance, nVidia, Package, Review, Tesla C2075

July 20, 2013 by hgpu

Intel Xeon Phi Coprocessor High-Performance Programming

Jim Jeffers, James Jeffers, James Reinders

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Tags: Book, Computer science, Intel, Intel Phi, OpenMP, Package, Review

June 30, 2013 by hgpu

Best Practice Guide – Intel Xeon Phi

Michaela Barth, Mikko Byckling, Nevena Ilieva, Sami Saarinen, Michael Schliephake, Volker Weinberg

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Tags: Computer science, Intel, Intel Phi, OpenMP, Review

June 30, 2013 by hgpu

Recent Advances on GPU Computing in Operations Research

incent Boyer, Didier El Baz

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Tags: Computer science, Review

June 10, 2013 by hgpu

Accelerating Financial Applications on the GPU

Scott Grauer-Gray, William Killian, Robert Searles, John Cavazos

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Tags: Computational finance, CUDA, Finance, nVidia, OpenACC, OpenCL, Package, Review, Tesla C2050, Tesla K20

May 6, 2013 by hgpu

Algorithms for representation of 3D regions in radiotherapy planning software

Jonny Gunnarsson

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Tags: Computer science, CUDA, Distance transform, nVidia, nVidia GeForce GTX 470, Radiotherapy, Review, Thesis

May 3, 2013 by hgpu

Graphics Programming on the Web WebCL Course Notes

Mikael Bourges-Sevenier

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Tags: Computer science, OpenCL, Review, Tutorial

May 1, 2013 by hgpu

A Discussion of Selected Vienna-Libraries for Computational Science

Karl Rupp, Florian Rudolf, Josef Weinbub

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, OpenCL, Programming techniques, Review

April 1, 2013 by hgpu

Massively Parallel Computing in Economics

Eric M. Aldrich

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Tags: CUDA, Finance, nVidia, Package, Review, Stochastic simulation, Tesla C2075

February 15, 2013 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

GPU-based simulation of brain neuron models

A Survey on GPU System Considering its Performance on Different Applications

Bitcoin and The Age of Bespoke Silicon

GPU Computing in Economics

Intel Xeon Phi Coprocessor High-Performance Programming

Best Practice Guide – Intel Xeon Phi

Recent Advances on GPU Computing in Operations Research

Accelerating Financial Applications on the GPU

Algorithms for representation of 3D regions in radiotherapy planning software

Graphics Programming on the Web WebCL Course Notes

A Discussion of Selected Vienna-Libraries for Computational Science

Massively Parallel Computing in Economics

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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