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hgpu.org » Applications » Computer science

Dense linear algebra solvers for multicore with GPU accelerators

Stanimire Tomov, Rajib Nath, Hatem Ltaief, Jack Dongarra

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Tags: Algorithms, Computer science, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280, Package

March 23, 2011 by hgpu

GPU Accelerators for Evolvable Cellular Automata

Ludek Zaloudek, Lukas Sekanina, Vaclav Simek

Tags: Cellular automata, Computer science, CUDA, Genetic programming, nVidia

March 23, 2011 by hgpu

Data Visualization and Mining using the GPU

Sudipto Guha

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Tags: Computer science, Data mining, Rendering, Review, Visualization

March 23, 2011 by hgpu

Efficient stream reduction on the GPU

David Roger, Ulf Assarsson, Nicolas Holzschuch

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce 8800 GTS, OpenGL, Programming techniques

March 23, 2011 by hgpu

Bridging the GPGPU-FPGA efficiency gap

Christopher W. Fletcher, Ilia A. Lebedev, Narges B. Asadi, Daniel R. Burke, John Wawrzynek

Tags: Algorithms, Bayesian, Computer science, FPGA, Heterogeneous systems, nVidia, OpenCL

March 22, 2011 by hgpu

Improving accuracy for matrix multiplications on GPUs

Matthew Badin, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Performance

March 22, 2011 by hgpu

Constructing Two-Dimensional Voronoi Diagrams via Divide-and-Conquer of Envelopes in Space (thesis)

Ophir Setter

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Tags: Algorithms, Computer science, Distance transform, Voronoi diagram

March 22, 2011 by hgpu

Constructing Two-Dimensional Voronoi Diagrams via Divide-and-Conquer of Envelopes in Space

Ophir Setter, Micha Sharir, Dan Halperin

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Tags: Algorithms, Computer science, Distance transform, Voronoi diagram

March 22, 2011 by hgpu

fastHOG – a real-time GPU implementation of HOG

Victor A. Prisacariu, Ian Reid

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 285, Package

March 22, 2011 by hgpu

Hierarchical belief propagation to reduce search space using CUDA for stereo and motion estimation

Scott Grauer-Gray, Chandra Kambhamettu

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 8600 M GT

March 22, 2011 by hgpu

GPU implementation of belief propagation using CUDA for cloud tracking and reconstruction

Scott Grauer-Gray, Chandra Kambhamettu, Kannappan Palaniappan

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 8800 GT

March 22, 2011 by hgpu

GPU-based password cracking

Marcus Bakker, Roel Van Der Jagt

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Review, Security

March 21, 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

Applications

Dense linear algebra solvers for multicore with GPU accelerators

GPU Accelerators for Evolvable Cellular Automata

Data Visualization and Mining using the GPU

Efficient stream reduction on the GPU

Bridging the GPGPU-FPGA efficiency gap

Improving accuracy for matrix multiplications on GPUs

Constructing Two-Dimensional Voronoi Diagrams via Divide-and-Conquer of Envelopes in Space (thesis)

Constructing Two-Dimensional Voronoi Diagrams via Divide-and-Conquer of Envelopes in Space

fastHOG – a real-time GPU implementation of HOG

Hierarchical belief propagation to reduce search space using CUDA for stereo and motion estimation

GPU implementation of belief propagation using CUDA for cloud tracking and reconstruction

GPU-based password cracking

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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