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OpenMPC: Extended OpenMP Programming and Tuning for GPUs

Seyong Lee, Rudolf Eigenmann

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, OpenMP

April 23, 2011 by hgpu

Automatically generating and tuning GPU code for sparse matrix-vector multiplication from a high-level representation

Dominik Grewe, Anton Lokhmotov

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Tags: ATI, ATI Radeon HD 5970, Code generation, Computer science, CUDA, High-level Languages, Linear Algebra, nVidia, OpenCL, Sparse matrix, Tesla S1070

April 21, 2011 by hgpu

Parallel Lexicographic Names Construction with CUDA

Weidong Sun, Zongmin Ma

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce 9600 GSO, Suffix trees

April 16, 2011 by hgpu

Automated development of applications for graphical processing units using rewriting rules

Anatoliy Yu. Doroshenko, Konstantin Zhereb

Tags: Code generation, Computer science, High-level Languages, Programming techniques

April 12, 2011 by hgpu

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

Andreas Klockner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih

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Tags: Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 9400 M, nVidia GeForce GTX 295, nVidia GeForce GTX 480, OpenCL, Package, PyOpenCL, Python, Software Engineering, Tesla C1060

March 30, 2011 by hgpu

Language virtualization for heterogeneous parallel computing

Hassan Chafi, Zach DeVito, Adriaan Moors, Tiark Rompf, Arvind K. Sujeeth, Pat Hanrahan, Martin Odersky, Kunle Olukotun

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Tags: Algorithms, Code generation, Computer science, Heterogeneous systems, High-level Languages

March 17, 2011 by hgpu

A framework for efficient and scalable execution of domain-specific templates on GPUs

Narayanan Sundaram, Anand Raghunathan, S. T. Chakradhar

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Tags: Code generation, Compilers, Computer science, nVidia, nVidia GeForce 8800 GTX, Tesla C870

March 15, 2011 by hgpu

Obsidian: GPU Programming in Haskell

Koen Claessen, Mary Sheeran, Joel Svensson

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, Package

March 13, 2011 by hgpu

Obsidian: GPU Kernel Programming in Haskell (thesis)

Joel Svensson

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 320 M, nVidia GeForce GTX 480, Package, Thesis

March 13, 2011 by hgpu

Automatic Generation of Multicore Chemical Kernels

John C. Linford, John Michalakes, Manish Vachharajani, Adrian Sandu

Tags: Cell processor, Chemistry, Code generation, Computer science, CUDA, nVidia, OpenMP

March 6, 2011 by hgpu

Automatic data movement and computation mapping for multi-level parallel architectures with explicitly managed memories

Muthu Manikandan Baskaran, Uday Bondhugula, Sriram Krishnamoorthy, J. Ramanujam, Atanas Rountev, P. Sadayappan

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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Performance

February 28, 2011 by hgpu

A Domain-Specific Approach To Heterogeneous Parallelism

Hassan Chafi, Arvind K. Sujeeth, Kevin J. Brown, HyoukJoong Lee, Anand R. Atreya, Kunle Olukotun

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia GeForce GTX 275

February 27, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

OpenMPC: Extended OpenMP Programming and Tuning for GPUs

Automatically generating and tuning GPU code for sparse matrix-vector multiplication from a high-level representation

Parallel Lexicographic Names Construction with CUDA

Automated development of applications for graphical processing units using rewriting rules

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

Language virtualization for heterogeneous parallel computing

A framework for efficient and scalable execution of domain-specific templates on GPUs

Obsidian: GPU Programming in Haskell

Obsidian: GPU Kernel Programming in Haskell (thesis)

Automatic Generation of Multicore Chemical Kernels

Automatic data movement and computation mapping for multi-level parallel architectures with explicitly managed memories

A Domain-Specific Approach To Heterogeneous Parallelism

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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