high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Multifrontal computations on GPUs and their multi-core hosts

Robert F. Lucas, Gene Wagenbreth, Dan M. Davis, Roger Grimes

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Tags: Computer science, CUDA, Factorization, nVidia, Performance, Sparse matrix, Tesla C1060

October 7, 2011 by hgpu

Run-time Reconfigurable Multiprocessors

Madhura Purnaprajna

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Tags: ATI, Computer science, FPGA, Hardware Architecture, nVidia, Performance, Thesis

October 7, 2011 by hgpu

CUDA performance analyzer

Aniruddha Dasgupta

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Tags: Analytical model, Computer science, CUDA, Fast multipole method, nVidia, Optimization, Performance, Tesla C1060, Thesis

October 6, 2011 by hgpu

Static GPU threads and an improved scan algorithm

Jens Breitbart

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 280, OpenCL, Performance, Presentation, Programming techniques

October 6, 2011 by hgpu

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

Mark Silberstein, Assaf Schuster, John D. Owens

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, Optimization, Package, Performance, Probability, Task scheduling, Tesla C2050

October 5, 2011 by hgpu

A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms

Allison S. Gehrke, Ilkyeun Ra, Daniel A. Connors

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Tags: Code generation, Computer science, Numerical simulation, nVidia, Optimization, Performance, PTX

October 5, 2011 by hgpu

Tranformation of CPU-based Applications To Leverage on Graphics Processors using CUDA

Fawnizu Azmadi Hussin, Anas Mohd Nazlee, Noohul Basheer Zain Ali

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Tags: Algorithms, Computer science, CUDA, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 260, Performance, Programming techniques, Security

October 3, 2011 by hgpu

GPU-Accelerated DNA Distance Matrix Computation

Zhi Ying, Xinhua Lin, Simon Chong-Wee See, Minglu Li

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Tags: ATI, ATI Radeon HD 5850, Bioinformatics, Biology, Genetics, nVidia, OpenCL, Performance, Tesla C2050

October 3, 2011 by hgpu

An Auto-tuning Solution to Data Streams Clustering in OpenCL

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: ATI, ATI Radeon HD 5870, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Optimization, Performance

October 3, 2011 by hgpu

Power Management and Optimization

Hari Sundararajan

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Tags: Computer science, CUDA, Energy-efficient computing, Green, nVidia, nVidia GeForce GTX 260, Performance, Thesis

October 2, 2011 by hgpu

Power-Efficient Accelerators for High-Performance Applications

Ganesh Suryanarayan Dasika

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Tags: Computer science, Energy-efficient computing, Performance, Thesis

October 2, 2011 by hgpu

PTask: Operating System Abstractions To Manage GPUs as Compute Devices

Christopher J. Rossbach, Jon Currey, Mark Silberstein, Baishakhi Ray, Emmett Witchel

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Tags: Computer science, CUDA, HLSL, nVidia, nVidia GeForce GT 230, nVidia GeForce GTX 470, nVidia GeForce GTX 580, OpenCL, Operating systems, Performance, Programming techniques

October 2, 2011 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

Multifrontal computations on GPUs and their multi-core hosts

Run-time Reconfigurable Multiprocessors

CUDA performance analyzer

Static GPU threads and an improved scan algorithm

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms

Tranformation of CPU-based Applications To Leverage on Graphics Processors using CUDA

GPU-Accelerated DNA Distance Matrix Computation

An Auto-tuning Solution to Data Streams Clustering in OpenCL

Power Management and Optimization

Power-Efficient Accelerators for High-Performance Applications

PTask: Operating System Abstractions To Manage GPUs as Compute Devices

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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