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Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Thilina Gunarathne, Bimalee Salpitikorala, Arun Chauhan, Geoffrey Fox

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Tags: Algorithms, Code generation, Computer science, nVidia, OpenCL, Optimization, Statistics, Tesla C1060

September 25, 2011 by hgpu

Automatic Translation of CUDA to OpenCL and Comparison of Performance Optimizations on GPUs

Deepthi Nandakumar

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Thesis

September 24, 2011 by hgpu

CU2CL: A CUDA-to-OpenCL Translator for Multi-and Many-core Architectures

Gabriel Martinez, Wu-chun Feng, Mark Gardner

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Code generation, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 280, OpenCL

September 24, 2011 by hgpu

An MDE Approach for Automatic Code Generation from MARTE to OpenCL

Antonio Wendell De Oliveira Rodrigues, Frederic Guyomarc'H, Jean-Luc Dekeyser

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Tags: Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, OpenCL

September 24, 2011 by hgpu

Embedding OpenCL in C++ for Expressive GPU Programming

Orion Lawlor

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Tags: ATI, ATI Radeon HD 6850, Benchmarking, Code generation, Computer science, GLSL, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 460 M, nVidia GeForce GTX 580, OpenCL, OpenGL, Package

September 23, 2011 by hgpu

Simple optimizations for an applicative array language for graphics processors

Bradford Larsen

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Optimization, Programming Languages, Programming techniques

September 23, 2011 by hgpu

Mint: realizing CUDA performance in 3D stencil methods with annotated C

Didem Unat, Xing Cai, Scott B. Baden

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Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenMP, Optimization, Package, Performance, Programming Languages, Tesla C1060

September 21, 2011 by hgpu

Nikola: embedding compiled GPU functions in Haskell

Geoffrey Mainland, Greg Morrisett

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Programming Languages, Tesla T10

September 14, 2011 by hgpu

AnySL: efficient and portable shading for ray tracing

Ralf Karrenberg, Dmitri Rubinstein, Philipp Slusallek, Sebastian Hack

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Tags: 3D Graphics and Realism, Code generation, Compilers, Computer science, nVidia, Package, Programming Languages, PTX, Raytracing, Rendering

September 13, 2011 by hgpu

Lightweight modular staging: a pragmatic approach to runtime code generation and compiled DSLs

Tiark Rompf, Martin Odersky

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Tags: Code generation, Computer science, Optimization, Programming Languages, Software Engineering

September 11, 2011 by hgpu

High-performance SIMT code generation in an active visual effects library

Jay L.T. Cornwall, Lee Howes, Paul H.J. Kelly, Phil Parsonage, Bruno Nicoletti

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Tags: Algorithms, Code generation, CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, Performance, Software Engineering, Visualization

September 11, 2011 by hgpu

MacroSS: macro-SIMDization of streaming applications

Amir H. Hormati, Yoonseo Choi, Mark Woh, Manjunath Kudlur, Rodric Rabbah, Trevor Mudge, Scott Mahlke

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Tags: Code generation, Compilers, Computer science, Optimization, Performance, Programming Languages

September 7, 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

Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Automatic Translation of CUDA to OpenCL and Comparison of Performance Optimizations on GPUs

CU2CL: A CUDA-to-OpenCL Translator for Multi-and Many-core Architectures

An MDE Approach for Automatic Code Generation from MARTE to OpenCL

Embedding OpenCL in C++ for Expressive GPU Programming

Simple optimizations for an applicative array language for graphics processors

Mint: realizing CUDA performance in 3D stencil methods with annotated C

Nikola: embedding compiled GPU functions in Haskell

AnySL: efficient and portable shading for ray tracing

Lightweight modular staging: a pragmatic approach to runtime code generation and compiled DSLs

High-performance SIMT code generation in an active visual effects library

MacroSS: macro-SIMDization of streaming applications

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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