high performance computing on graphics processing units: hgpu.org

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Image registration on GPU

Jeremy Coatelen, Yu Qi

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Tags: Algorithms, ATI, ATI Mobility Radeon HD 5850, Cloud, Image processing, Image registration, nVidia, OpenCL

October 1, 2011 by hgpu

Real-Time Handling of GPU Interrupts in LITMUSRT

Glenn A. Elliott, Chih-Hao Sun, and James H. Anderson

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, Operating systems

September 30, 2011 by hgpu

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

Bo Wu, Eddy Z. Zhang, Xipeng Shen

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Tags: Algorithms, Benchmarking, CMP, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Tesla S1070

September 30, 2011 by hgpu

CBench: Analyzing Compute Performance for Modern NVIDIA and AMD GPUs

Varun Sampath

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Source codes

Tags: Algorithms, ATI, ATI Radeon HD 6870, Benchmarking, Computer science, CUDA, nVidia, OpenCL, Package, Tesla C2070

September 30, 2011 by hgpu

Translating GPU binaries to tiered SIMD architectures with Ocelot

Gregory Diamos, Andrew Kerr, Mukil Kesavan

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Tags: Algorithms, Cell processor, Compilers, Computer science, nVidia, PTX

September 30, 2011 by hgpu

Accelerating Geospatial Analysis on GPUs using CUDA

Ying-jie Xia, Li Kuang, Xiu-mei Li

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Tags: Algorithms, CUDA, Earth and Space Sciences, Geoscience, nVidia, nVidia Quadro FX 5600

September 30, 2011 by hgpu

Many-threaded implementation of differential evolution for the CUDA platform

Pavel Kromer, Vaclav Snasel, Jan Platos, Ajith Abraham

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential evolution, Genetic programming, nVidia, Optimization, Tesla C2050

September 29, 2011 by hgpu

Highly Scalable Multi Objective Test Suite Minimisation Using Graphics Cards

Shin Yoo, Mark Harman, Shmuel Ur

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Tags: Algorithms, ATI, ATI Radeon HD 4850, Benchmarking, Computer science, OpenCL, Optimization, Software Engineering

September 28, 2011 by hgpu

Global optimization model on power efficiency of GPU and multicore processing element for SIMD computing with CUDA

Da-Qi Ren, Reiji Suda

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 8800 GTS, Optimization, Tesla C2050

September 28, 2011 by hgpu

Fast On-line Statistical Learning on a GPGPU

FangZhou Xiao, Eric McCreath, Christfried Webers

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 200, nVidia GeForce GTX 295, Stochastic simulation

September 27, 2011 by hgpu

Intelligent GPGPU Classification in Volume Visualization: A framework based on Error-Correcting Output Codes

S. Escalera, A. Puig, O. Amoros, M. Salamo

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Tags: Algorithms, ATI, Computer science, Machine learning, nVidia, nVidia GeForce GTX 470, OpenCL, Rendering, Visualization

September 27, 2011 by hgpu

Manycore high-performance computing in bioinformatics

Jean-Stephane Varre, Bertil Schmidt, Stephane Janot, Mathieu Giraud

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, OpenCL, Review, RNA, Sequence alignment

September 26, 2011 by hgpu

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Real-Time Handling of GPU Interrupts in LITMUSRT

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

CBench: Analyzing Compute Performance for Modern NVIDIA and AMD GPUs

Translating GPU binaries to tiered SIMD architectures with Ocelot

Accelerating Geospatial Analysis on GPUs using CUDA

Many-threaded implementation of differential evolution for the CUDA platform

Highly Scalable Multi Objective Test Suite Minimisation Using Graphics Cards

Global optimization model on power efficiency of GPU and multicore processing element for SIMD computing with CUDA

Fast On-line Statistical Learning on a GPGPU

Intelligent GPGPU Classification in Volume Visualization: A framework based on Error-Correcting Output Codes

Manycore high-performance computing in bioinformatics

Recent source codes

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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