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Parallel graduated assignment algorithm for multiple graph matching based on a common labelling

David Rodenas, Francesc Serratosa, Albert Sole-Ribalta

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia ION, Presentation

September 21, 2011 by hgpu

GPU-based cloud performance for LiDAR data processing

Ramanathan Sugumaran, Dossay Oryspayev, Paul Gray

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Tags: Algorithms, Cloud, Computer science, CUDA, Data mining, Databases, Earth and Space Sciences, nVidia, Performance

September 21, 2011 by hgpu

Mint: realizing CUDA performance in 3D stencil methods with annotated C

Didem Unat, Xing Cai, Scott B. Baden

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Source codes

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenMP, Optimization, Package, Performance, Programming Languages, Tesla C1060

September 21, 2011 by hgpu

Automatic abstraction and fault tolerance in cortical microachitectures

Atif Hashmi, Hugues Berry, Olivier Temam, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Fault simulation, nVidia, nVidia GeForce 9800 GT

September 20, 2011 by hgpu

Brief announcement: better speedups for parallel max-flow

George Constantin Caragea, Uzi Vishkin

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Tags: Algorithms, ASIC, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 280, Performance

September 20, 2011 by hgpu

EFFEX: an embedded processor for computer vision based feature extraction

Jason Clemons, Andrew Jones, Robert Perricone, Silvio Savarese, Todd Austin

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 210, nVidia GeForce GTX 260, SIFT

September 20, 2011 by hgpu

Supporting GPU sharing in cloud environments with a transparent runtime consolidation framework

Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar

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Tags: Algorithms, Cloud, Computer science, CUDA, nVidia, Operating systems, Performance, Tesla C2050, Virtualization

September 20, 2011 by hgpu

Acceleration of genetic algorithms for sudoku solution on many-core processors

Yuji Sato, Naohiro Hasegawa, Mikiko Sato

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Tags: Algorithms, Computer science, CUDA, Games, Genetic programming, nVidia, nVidia GeForce GTX 460, Presentation

September 20, 2011 by hgpu

Parallel divide-and-evolve: experiments with OpenMP on a multicore machine

Caner Candan, Johann Dreo, Pierre Saveant, Vincent Vidal

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Tags: Algorithms, Artificial intelligence, Computer science, Evolutionary Computations, Metaheuristics, Programming techniques

September 19, 2011 by hgpu

DAMS: distributed adaptive metaheuristic selection

Bilel Derbel, Sebastien Verel

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Tags: Algorithms, Computer science, Metaheuristics, Optimization, Presentation

September 19, 2011 by hgpu

Real-time ray casting of algebraic B-spline surfaces

Feifei Wei, Jieqing Feng

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Interactive application, nVidia, nVidia GeForce GTX 570, Rasterization, Real-time graphics, Visualization

September 19, 2011 by hgpu

Improving SIMD efficiency for parallel Monte Carlo light transport on the GPU

Dietger van Antwerpen

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing

September 19, 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

Parallel graduated assignment algorithm for multiple graph matching based on a common labelling

Mint: realizing CUDA performance in 3D stencil methods with annotated C

Automatic abstraction and fault tolerance in cortical microachitectures

Brief announcement: better speedups for parallel max-flow

EFFEX: an embedded processor for computer vision based feature extraction

Acceleration of genetic algorithms for sudoku solution on many-core processors

Parallel divide-and-evolve: experiments with OpenMP on a multicore machine

DAMS: distributed adaptive metaheuristic selection

Real-time ray casting of algebraic B-spline surfaces

Improving SIMD efficiency for parallel Monte Carlo light transport on the GPU

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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