high performance computing on graphics processing units: hgpu.org

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Convergence and Scalarization for Data-Parallel Architectures

Yunsup Lee, Ronny Krashinsky, Vinod Grover, Stephen W. Keckler, Krste Asanovic

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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, Data parallelism, nVidia, Performance

March 15, 2013 by hgpu

Automatic efficient data layout for multithreaded stencil codes on CPUs and GPUs

Julien Jaeger, Denis Barthou

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro FX 5800

March 12, 2013 by hgpu

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Malik Muhammad Zaki Murtaza Khan

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Tags: Code generation, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050, Thesis

January 26, 2013 by hgpu

Interactive Refactoring for GPU Parallelization of Affine Loops

Kostadin Damevski, Madhan Muralimanohar

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 2000

January 7, 2013 by hgpu

Automatic Code Generation for Stencil Computations on GPU Architectures

Justin Andrew Holewinski

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenCL, Tesla C2050, Tesla K10, Thesis

January 4, 2013 by hgpu

Towards Domain-specific Computing for Stencil Codes in HPC

Richard Membarth, Frank Hannig, Jurgen Teich, Harald Kostler

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Tags: Algorithms, Code generation, Compression, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Package, Tesla C2050

December 12, 2012 by hgpu

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

Tiark Rompf

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Software Engineering, Tesla C2050, Thesis

December 8, 2012 by hgpu

Developing Extensible Lattice-Boltzmann Simulators for General-Purpose Graphics-Processing Units

Stuart D. C. Walsh, Martin O. Saar

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Tags: Code generation, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C1060

December 1, 2012 by hgpu

A compiler toolkit for array-based languages targeting CPU/GPU hybrid systems

Rahul Garg, Laurie Hendren

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 7970, Code generation, Compilers, Computer science, OpenCL, Package, Python, Tesla C2050

November 26, 2012 by hgpu

Auto-tuning on the macro scale: high level algorithmic auto-tuning for scientific applications

Cy P Chan

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Tags: Algorithms, Code generation, Computer science, nVidia, nVidia GeForce GTX 280, Optimization, Thesis

November 23, 2012 by hgpu

Sigma*: Symbolic Learning of Input-Output Specifications

Matko Botincan, Domagoj Babic

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Programming Languages

November 10, 2012 by hgpu

GPU Virtualization

Kristoffer Robin Stokke

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro NVS 295, Package, Python, Thesis, Virtualization

November 7, 2012 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

Convergence and Scalarization for Data-Parallel Architectures

Automatic efficient data layout for multithreaded stencil codes on CPUs and GPUs

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Interactive Refactoring for GPU Parallelization of Affine Loops

Automatic Code Generation for Stencil Computations on GPU Architectures

Towards Domain-specific Computing for Stencil Codes in HPC

Lightweight Modular Staging and Embedded Compilers: Abstraction Without Regret for High-Level High-Performance Programming

Developing Extensible Lattice-Boltzmann Simulators for General-Purpose Graphics-Processing Units

A compiler toolkit for array-based languages targeting CPU/GPU hybrid systems

Auto-tuning on the macro scale: high level algorithmic auto-tuning for scientific applications

Sigma*: Symbolic Learning of Input-Output Specifications

GPU Virtualization

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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