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Ray Traced Rendering Using GPGPU Devices

Coby Soss

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Tags: ATI, ATI Mobility Radeon HD 5870, Computer science, OpenCL, Raytracing, Rendering, Thesis

September 11, 2014 by hgpu

Enhancing R with Advanced Compilation Tools and Methods

Duncan Temple Lang

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Tags: Computer science, CUDA, Mathematical Software, nVidia, Programming Languages

September 11, 2014 by hgpu

Parallel Multi-dimensional Range Query Processing with R-Trees on GPU

Jinwoong Kim, Beomseok Nam

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Tags: Algorithms, Computer science, CUDA, Databases, Indexing, nVidia, Tesla M2090

September 9, 2014 by hgpu

Improvements to Physically Based Cloth Simulation

Tsz Ho Wong

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Tags: 3D Graphics and Realism, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 780, Review, Thesis

September 9, 2014 by hgpu

A Validation Testsuite for OpenACC 1.0

Cheng Wang, Rengan Xu, Sunita Chandrasekaran, Barbara Chapman, Oscar Hernandez

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Tags: Compilers, Computer science, Fortran, nVidia, OpenACC, Tesla K20

September 9, 2014 by hgpu

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

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Tags: Algorithms, Biology, CUDA, Genetics, Machine learning, Neuroscience, nVidia, nVidia GeForce GTX Titan, Statistics

September 9, 2014 by hgpu

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Gary K. Chen, Eric Chi, John Ranola, Kenneth Lange

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Tags: Algorithms, Bioinformatics, Biology, Cluster analysis, Clustering, Genomics, Hierarchical clustering, nVidia, OpenCL, Package, Tesla C2050

September 9, 2014 by hgpu

Professional CUDA C Programming

John Cheng, Max Grossman, Ty McKercher

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Tags: Algorithms, Book, Computer science, CUDA, Memory model, nVidia, Review

September 8, 2014 by hgpu

Document Classification Using KNN on GPU

S.G. Lade, Nikhil Vyawahare

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 520 M, Text mining

September 8, 2014 by hgpu

Sparse array representations and some selected array operations on GPUs

Hairong Wang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 670, Sparse matrix, Thesis

September 8, 2014 by hgpu

A CUDA Back-End for the Equelle Compiler

Havard Heitlo Holm

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Tags: Compilers, Computer science, CUDA, Differential equations, Finite volume method, Heterogeneous systems, nVidia, nVidia Quadro NVS 5200 M, Package, Partial differential equations, PDEs, Tesla K40, Thesis

September 8, 2014 by hgpu

Accelerated Combinatorial Optimization using Graphics Processing Units and C++ AMP

Alexandru Voicu

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Tags: Algorithm optimization, Ant colony optimization, C++ AMP

September 8, 2014 by AlexVlx

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

ThunderKittens: Tile primitives for speedy kernels

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

NVIDIA Nemotron Parse 1.1

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

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Ray Traced Rendering Using GPGPU Devices

Enhancing R with Advanced Compilation Tools and Methods

Parallel Multi-dimensional Range Query Processing with R-Trees on GPU

Improvements to Physically Based Cloth Simulation

A Validation Testsuite for OpenACC 1.0

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Professional CUDA C Programming

Document Classification Using KNN on GPU

Sparse array representations and some selected array operations on GPUs

A CUDA Back-End for the Equelle Compiler

Accelerated Combinatorial Optimization using Graphics Processing Units and C++ AMP

Recent source codes

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

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

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

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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