high performance computing on graphics processing units: hgpu.org

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A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

Allen Leung, Nicolas Vasilache, Benoit Meister, Muthu Baskaran, David Wohlford, Cedric Bastoul, Richard Lethin

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Tags: Algorithms, Code generation, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 285, Programming Languages

August 24, 2011 by hgpu

CnC-CUDA: declarative programming for GPUs

Max Grossman, Alina Simion Sbirlea, Zoran Budimlic, Vivek Sarkar

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 480, Performance

August 24, 2011 by hgpu

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system

Linchuan Li, Xingjian Li, Guangming Tan, Mingyu Chen, Peiheng Zhang

Tags: Algorithms, Computer science, Cryo-EM, CUDA, Data parallelism, GPU cluster, Heterogeneous systems, MPI, nVidia, Performance, Tesla C2050

August 24, 2011 by hgpu

JCudaMP: OpenMP/Java on CUDA

Georg Dotzler, Ronald Veldema, Michael Klemm

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Tags: Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 280, OpenMP, Programming Languages, Programming techniques

August 23, 2011 by hgpu

Implementing the PGI Accelerator model

Michael Wolfe

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization, Programming Languages, Tesla C1060, Tesla S1070

August 23, 2011 by hgpu

Bounding the effect of partition camping in GPU kernels

Ashwin M. Aji, Mayank Daga, Wu-chun Feng

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, Performance

August 23, 2011 by hgpu

Fast parallel surface and solid voxelization on GPUs

Michael Schwarz, Hans-Peter Seidel

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480

August 23, 2011 by hgpu

High performance content-based matching using GPUs

Alessandro Margara, Gianpaolo Cugola

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Tags: Algorithms, Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 460, Package, Performance, Programming techniques

August 23, 2011 by hgpu

Performance Modelling and Traffic Characterisation of Optical Networks

Harry Mouchos, Athanasios Tsokanos and Demetres D. Kouvatsos

Tags: Computer science, CUDA, Network communications, Networks, nVidia

August 23, 2011 by hgpu

Auto-tuning 3-D FFT library for CUDA GPUs

Akira Nukada, Satoshi Matsuoka

Tags: Algorithms, Computer science, CUDA, FFT, Mathematical Software, nVidia, Performance

August 22, 2011 by hgpu

Evaluation of streaming aggregation on parallel hardware architectures

Scott Schneidert, Henrique Andrade, Bugra Gedik, Kun-Lung Wu, Dimitrios S. Nikolopoulos

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Tags: Cell processor, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, OpenMP, Performance

August 22, 2011 by hgpu

Floating-point data compression at 75 Gb/s on a GPU

Molly A. O'Neil, Martin Burtscher

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce FX 5600, Package, Performance, Programming techniques

August 22, 2011 by hgpu

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

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

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high performance computing on graphics processing units: hgpu.org

A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction

CnC-CUDA: declarative programming for GPUs

Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system

JCudaMP: OpenMP/Java on CUDA

Implementing the PGI Accelerator model

Bounding the effect of partition camping in GPU kernels

Fast parallel surface and solid voxelization on GPUs

High performance content-based matching using GPUs

Performance Modelling and Traffic Characterisation of Optical Networks

Auto-tuning 3-D FFT library for CUDA GPUs

Evaluation of streaming aggregation on parallel hardware architectures

Floating-point data compression at 75 Gb/s on a GPU

Recent source codes

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

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

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