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Autotuning Tensor Contraction Computations on GPUs

Axel Rivera, Mary Hall, Paul D. Hovland, Elizabeth Jessup, Thomas Nelson, Boyana Norris

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Tags: Benchmarking, Code generation, Computer science, CUDA, Matrix multiplication, nVidia, OpenACC, Tesla C2050, Tesla K20

June 19, 2015 by hgpu

Type-safe Runtime Code Generation: Accelerate to LLVM

Trevor L. McDonell, Manuel M. T. Chakravarty, Vinod Grover, Ryan R. Newton

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Sparse matrix, Tesla K40

June 14, 2015 by hgpu

OMP2HMPP: Compiler Framework for Energy-Performance Trade-off Analysis of Automatically Generated Codes

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, Tesla M2050

May 5, 2015 by hgpu

IPMACC: Translating OpenACC API to OpenCL

Ahmad Lashgar, Alireza Majidi, Amirali Baniasadi

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Tags: Code generation, Computer science, CUDA, nVidia, OpenACC, OpenCL, Package, Tesla K20

May 3, 2015 by hgpu

Loo.py: From Fortran to performance via transformation and substitution rules

Andreas Klockner

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Tags: Code generation, Computer science, Fortran, OpenCL, Package, Python

March 28, 2015 by hgpu

Generating Performance Portable Code using Rewrite Rules: From High-level Functional Expressions to High-Performance OpenCL Code

Michel Steuwer, Christian Fensch, Sam Lindley, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

March 8, 2015 by hgpu

Patterns and Rewrite Rules for Systematic Code Generation (From High-Level Functional Patterns to High-Performance OpenCL Code)

Michel Steuwer, Christian Fensch, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Programming Languages

February 10, 2015 by hgpu

Pointer Analysis for Semi-Automatic Code Parallelizers

Ketan Sudhakar Vyavahare

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Tags: Code generation, Computer science, CUDA, OpenCL, Thesis

February 3, 2015 by hgpu

An Extensible Framework for Composing Stencils with Common Scientific Computing Patterns

Leonard Truong, Chick Markley, Armando Fox

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Tags: Code generation, Computer science, OpenCL, Python

January 8, 2015 by hgpu

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

Naresh Balaji, Esin Yavuz, Thomas Nowotny

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Tags: Algorithms, Code generation, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GT 755 M, Package

December 2, 2014 by hgpu

GPU Declarative Framework

Robert W. Senser, Jr.

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Tags: AMD Radeon R9 270, ATI, Code generation, Computer science, Filtering, Image processing, Matrix inversion, nVidia, OpenCL, Sorting, Tesla S2050, Tesla T20, Thesis

December 1, 2014 by hgpu

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

G.R. Mudalige, I.Z. Reguly, M.B. Giles, A.C. Mallinson, W.P. Gaudin, J.A. Herdman

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenACC, OpenCL, Tesla K20

December 1, 2014 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

Autotuning Tensor Contraction Computations on GPUs

Type-safe Runtime Code Generation: Accelerate to LLVM

OMP2HMPP: Compiler Framework for Energy-Performance Trade-off Analysis of Automatically Generated Codes

IPMACC: Translating OpenACC API to OpenCL

Loo.py: From Fortran to performance via transformation and substitution rules

Generating Performance Portable Code using Rewrite Rules: From High-level Functional Expressions to High-Performance OpenCL Code

Patterns and Rewrite Rules for Systematic Code Generation (From High-Level Functional Patterns to High-Performance OpenCL Code)

Pointer Analysis for Semi-Automatic Code Parallelizers

An Extensible Framework for Composing Stencils with Common Scientific Computing Patterns

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

GPU Declarative Framework

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

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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