high performance computing on graphics processing units: hgpu.org

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Bothnia: a dual-personality extension to the Intel integrated graphics driver

Gautham N. Chinya, Jamison D. Collins, Perry H. Wang, Hong Jiang, Guei Y. Lueh, Thomas A. Piazza, Hong Wang

Tags: Computer science, Intel, Intel GMA X3000, Programming techniques

February 28, 2011 by hgpu

Data Buffering Optimization Methods toward a Uniform Programming Interface for GPU-based Applications

Shinichi Yamagiwa, Leonel Sousa, Diogo Antao

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Tags: Computer science, DirectX, nVidia, nVidia GeForce 7400 GO, OpenGL, Programming techniques

February 27, 2011 by hgpu

Accelerating CUDA Graph Algorithms at Maximum Warp

Sungpack Hong, Sang Kyun Kim, Tayo Oguntebi, Kunle Olukotun

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, Package, Performance, Programming techniques

February 27, 2011 by hgpu

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Rajesh Bordawekar, Uday Bondhugula, Ravi Rao

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Performance, Programming techniques

February 26, 2011 by hgpu

Concurrent GPU Programming

Lesley Northam

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 M GTX, Programming techniques, Review

February 26, 2011 by hgpu

Pyramid Methods in GPU-Based Image Processing

Magnus Strengert, Martin Kraus, and Thomas Ertl

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Tags: Algorithms, Image processing, nVidia, nVidia GeForce 7800 GTX, OpenGL, Programming techniques

February 25, 2011 by hgpu

Program Optimization Study on a 128-Core GPU

Shane Ryoo, Christopher I. Rodrigues, Sam S. Stone, Sara S. Baghsorkhi, Sain-Zee Ueng, and Wen-mei W. Hwu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Programming techniques

February 20, 2011 by hgpu

Efficient compilation of fine-grained SPMD-threaded programs for multicore CPUs

John A. Stratton, Vinod Grover, Jaydeep Marathe, Bastiaan Aarts, Mike Murphy, Ziang Hu, Wen-mei W. Hwu

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenCL, Programming techniques

February 20, 2011 by hgpu

Accelerating Cosmological Data Analysis with Graphics Processors

Dylan W. Roeh, Volodymyr V. Kindratenko, Robert J. Brunner

Tags: Astrophysics, Cosmology, CUDA, GPU cluster, MPI, nVidia, Physics, Programming techniques

February 15, 2011 by hgpu

Partitioning streaming parallelism for multi-cores: a machine learning based approach

Zheng Wang, Michael F. P. O'Boyle

Tags: Computer science, Optimization, Programming techniques

February 8, 2011 by hgpu

XMT-GPU: A PRAM Architecture for Graphics Computation

Thomas M. DuBois, Bryant Lee, Yi Wang, Marc Olano, Uzi Vishkin

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Tags: Algorithms, ATI, ATI Radeon X700 Pro, Computer science, nVidia, nVidia GeForce 7900 GTX, nVidia GeForce 8800 GTX, OpenGL, Programming techniques

February 6, 2011 by hgpu

Evaluating multi-core platforms for HPC data-intensive kernels

Alexander S. van Amesfoort, Ana Lucia Varbanescu, Henk J. Sips, Rob V. van Nieuwpoort

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Tags: Algorithms, Cell processor, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Programming techniques, Tesla C1060

February 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

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high performance computing on graphics processing units: hgpu.org

Bothnia: a dual-personality extension to the Intel integrated graphics driver

Data Buffering Optimization Methods toward a Uniform Programming Interface for GPU-based Applications

Accelerating CUDA Graph Algorithms at Maximum Warp

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Concurrent GPU Programming

Pyramid Methods in GPU-Based Image Processing

Program Optimization Study on a 128-Core GPU

Efficient compilation of fine-grained SPMD-threaded programs for multicore CPUs

Accelerating Cosmological Data Analysis with Graphics Processors

Partitioning streaming parallelism for multi-cores: a machine learning based approach

XMT-GPU: A PRAM Architecture for Graphics Computation

Evaluating multi-core platforms for HPC data-intensive kernels

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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