Programming techniques | Page 25

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Introduction to GPGPU programming

Jay E. Steele, Robert Cochran

Tags: Computer science, High-level Languages, Programming techniques, Review

December 29, 2010 by hgpu

A code motion technique for accelerating general-purpose computation on the GPU

Takatoshi Ikeda, Fumihiko Ino, and Kenichi Hagihar

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Tags: Computer science, nVidia, nVidia GeForce 6800, OpenGL, Programming techniques

December 24, 2010 by hgpu

Fine-grain Parallelism Using Multi-core, Cell/BE, and GPU Systems: Accelerating the Phylogenetic Likelihood Function

Frederico Pratas, Pedro Trancoso, Alexandros Stama

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Tags: Cell processor, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, Performance, Programming techniques

December 24, 2010 by hgpu

Parallel Branch Prediction on GPU Platform

Liqiang He, Guangyong Zhang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9600 GT, Programming techniques

December 22, 2010 by hgpu

Pushing the Envelope: Extreme Network Coding on the GPU

Hassan Shojania, Baochun Li

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques

December 22, 2010 by hgpu

GPU Acceleration of Iterative Clustering

Jesse D. Hall, John C. Hart

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce FX 5900 Ultra, OpenGL, Programming techniques

December 21, 2010 by hgpu

GPU-based parallelization for fast circuit optimization

Yifang Liu, Jiang Hu

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Tags: Computer science, CUDA, Hardware, nVidia, nVidia GeForce 9800 GT, Programming techniques

December 19, 2010 by hgpu

Large-scale FFT on GPU clusters

Yifeng Chen, Xiang Cui, Hong Mei

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 285, Programming techniques, Tesla C1060

December 18, 2010 by hgpu

GPU Parallelization of Algebraic Dynamic Programming

Peter Steffen, Robert Giegerich, Mathieu Giraud

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Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Package, Presentation, Programming techniques

December 17, 2010 by hgpu

Revolutionary technologies for acceleration of emerging petascale applications

Rupak Biswas, Leonid Oliker and Jeffrey Vetter

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Tags: Computer science, Programming techniques

December 16, 2010 by hgpu

OpenMP to GPGPU: a compiler framework for automatic translation and optimization

Seyong Lee, Seung-Jai Min, and Rudolf Eigenman

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia Quadro FX 5600, OpenMP, Programming techniques

December 15, 2010 by hgpu

Scalable Programming Models for Massively Multicore Processors

M. D. McCool

Tags: Cell processor, Computer science, Programming techniques

December 14, 2010 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

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high performance computing on graphics processing units: hgpu.org

Introduction to GPGPU programming

A code motion technique for accelerating general-purpose computation on the GPU

Fine-grain Parallelism Using Multi-core, Cell/BE, and GPU Systems: Accelerating the Phylogenetic Likelihood Function

Parallel Branch Prediction on GPU Platform

Pushing the Envelope: Extreme Network Coding on the GPU

GPU Acceleration of Iterative Clustering

GPU-based parallelization for fast circuit optimization

Large-scale FFT on GPU clusters

GPU Parallelization of Algebraic Dynamic Programming

Revolutionary technologies for acceleration of emerging petascale applications

OpenMP to GPGPU: a compiler framework for automatic translation and optimization

Scalable Programming Models for Massively Multicore Processors

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

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

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