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Accelerating Large Scale Image Analyses on Parallel CPU-GPU Equipped Systems

George Teodoro, Tahsin M. Kurc, Tony Pan, Lee Cooper, Jun Kong, Patrick Widener, Joel H. Saltz

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Tags: CUDA, Heterogeneous systems, Image processing, nVidia, Tesla M2070

October 14, 2011 by hgpu

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

Michael Bauer, Henry Cook, Brucek Khailany

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Tags: Benchmarking, Computer science, CUDA, Memory model, nVidia, Optimization, Package, Performance, Tesla C2050

October 14, 2011 by hgpu

Liszt: A Domain Specific Language for Building Portable Mesh-based PDE Solvers

Zachary DeVito, Niels Joubert, Francisco Palacios, Stephen Oakley, Montserrat Medina, Mike Barrientos, Erich Elsen, Frank Ham, Alex Aiken, Karthik Duraisamy, Eric Darve, Juan Alonso, Pat Hanrahan

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 14, 2011 by hgpu

GPU Computing Gems: Jade Edition

Wen-mei W. Hwu

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Tags: Algorithms, Book, Cellular automata, Computational finance, Computer science, Computer vision, CUDA, Finance, Fluid dynamics, Games, GPU cluster, nVidia

October 14, 2011 by hgpu

Towards scalar synchronization in SIMT architectures

Arun Ramamurthy

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Tags: Benchmarking, Computer science, CUDA, nVidia, OpenCL, Performance, Programming techniques, Thesis

October 14, 2011 by hgpu

Fast Multipole Method vs. Spectral Method for the Simulation of Isotropic Turbulence on GPUs

Rio Yokota, L. A. Barba

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Tags: Algorithms, Computational Physics, CUDA, Fast multipole method, FFT, Fluid dynamics, Numerical Analysis, nVidia, Spectral methods, Tesla C2070

October 14, 2011 by hgpu

Benchmarking Across Platforms: European Option Pricing

Igor N. Kozin

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Tags: AMD FireStream 9270, Benchmarking, Cell processor, Computer science, CUDA, Finance, nVidia, OpenCL, Tesla M2050, Tesla S1070

October 13, 2011 by hgpu

Input Sensitivity of GPU Program Optimizations

Yixun Liu, Eddy Z. Zhang, Poornima Bhamidipati, Xipeng Shen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, OpenCL, Optimization, Performance, Tesla C1060

October 13, 2011 by hgpu

gpustats: GPU Library for Statistical Computing in Python

Andrew Cron, Wes McKinney

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Tags: Algorithms, Bayesian, Code generation, CUDA, Mathematics, nVidia, nVidia GeForce GTS 250, OpenCL, Package, Probability, Python, Statistics

October 13, 2011 by hgpu

Developing a High Performance GPGPU Compiler Using Cetus

Yi Yang, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5850, ATI Radeon HD 5870, Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization

October 13, 2011 by hgpu

PlinkGPU: A Framework for GPU Acceleration of Whole Genome Data Analysis

Jeffrey Poznanovic

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, OpenCL, Tesla S1070

October 13, 2011 by hgpu

State of The Art Report on GPU

Rita Borgo, Ken Brodlie

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Tags: Computer science, CUDA, DirectX, GLSL, GPU cluster, Hardware, HLSL, Larrabee, nVidia, OpenGL, Programming techniques, Review

October 13, 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

Programming

Accelerating Large Scale Image Analyses on Parallel CPU-GPU Equipped Systems

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

Liszt: A Domain Specific Language for Building Portable Mesh-based PDE Solvers

GPU Computing Gems: Jade Edition

Towards scalar synchronization in SIMT architectures

Fast Multipole Method vs. Spectral Method for the Simulation of Isotropic Turbulence on GPUs

Benchmarking Across Platforms: European Option Pricing

Input Sensitivity of GPU Program Optimizations

gpustats: GPU Library for Statistical Computing in Python

Developing a High Performance GPGPU Compiler Using Cetus

PlinkGPU: A Framework for GPU Acceleration of Whole Genome Data Analysis

State of The Art Report on GPU

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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