high performance computing on graphics processing units: hgpu.org

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Parallel processing on NVIDIA graphics processing units using CUDA

Erik Wynters

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Tags: Computer science, CUDA, Education, nVidia, nVidia GeForce 9800 GT, Tutorial

September 23, 2011 by hgpu

Image super-resolution by vectorizing edges

Chia-Jung Hung, Chun-Kai Huang, Bing-Yu Chen

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Tags: Algorithms, Image processing

September 23, 2011 by hgpu

Acceleration of Functional Validation Using GPGPU

Lalith Suresh, Navaneeth Rameshan, M. S. Gaur, Mark Zwolinski, Vijay Laxmi

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Tags: Algorithms, Benchmarking, Computer science, Electronic design automation, nVidia, nVidia Quadro FX 1700, Tesla C870

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

HHT-based time-frequency analysis method for biomedical signal applications

Chin-Feng Lin, Jin-De Zhu

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Tags: Algorithms, Medicine, Signal processing, Wavelet

September 23, 2011 by hgpu

Compact data structure and scalable algorithms for the sparse grid technique

Alin Murarasu, Josef Weidendorfer, Gerrit Buse, Daniel Butnaru, Dirk Pfluger

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Tags: Algorithms, Compression, Computer science, CUDA, Numerical Analysis, nVidia, Optimization, Programming techniques, Tesla C1060

September 23, 2011 by hgpu

Colored stochastic shadow maps

Morgan McGuire, Eric Enderton

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Tags: 3D Graphics and Realism, Algorithms, Computer science, Image generation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Presentation

September 23, 2011 by hgpu

Unstructured grid applications on GPU: performance analysis and improvement

Lizandro Solano-Quinde, Zhi Jian Wang, Brett Bode, Arun K. Somani

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Software Engineering, Tesla T10

September 23, 2011 by hgpu

Orchestration by approximation: mapping stream programs onto multicore architectures

Sardar M. Farhad, Yousun Ko, Bernd Burgstaller, Bernhard Scholz

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Tags: Algorithms, Benchmarking, Compilers, Computer science, Optimization, Performance, Programming Languages

September 23, 2011 by hgpu

Quantifying NUMA and contention effects in multi-GPU systems

Kyle Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla M2070

September 23, 2011 by hgpu

Register packing for cyclic reduction: a case study

Andrew Davidson, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GTX 460, Performance

September 22, 2011 by hgpu

On-the-fly elimination of dynamic irregularities for GPU computing

Eddy Z. Zhang, Yunlian Jiang, Ziyu Guo, Kai Tian, Xipeng Shen

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Optimization, Performance, Programming Languages, Tesla C1060

September 22, 2011 by hgpu

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

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

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Parallel processing on NVIDIA graphics processing units using CUDA

Image super-resolution by vectorizing edges

Acceleration of Functional Validation Using GPGPU

Simple optimizations for an applicative array language for graphics processors

HHT-based time-frequency analysis method for biomedical signal applications

Compact data structure and scalable algorithms for the sparse grid technique

Colored stochastic shadow maps

Unstructured grid applications on GPU: performance analysis and improvement

Orchestration by approximation: mapping stream programs onto multicore architectures

Quantifying NUMA and contention effects in multi-GPU systems

Register packing for cyclic reduction: a case study

On-the-fly elimination of dynamic irregularities for GPU computing

Recent source codes

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

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

Most viewed papers (last 30 days)