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A Straightforward Preprocessing Approach for Accelerating Convex Hull Computations on the GPU

Gang Mei

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Tags: Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GT 640

May 16, 2014 by hgpu

Real-time Image Processing on Low Cost Embedded Computers

Sunil Shah

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Tags: ARM, Computer vision, Image processing, OpenCV, Package, Performance, Thesis

May 15, 2014 by hgpu

Parallelization of Shape Diameter Function Computation using OpenCL

Rastislav Kamenicky

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Tags: 3D Graphics and Realism, Algorithms, AMD Radeon R9 290, ATI, Computer science, OpenCL

May 15, 2014 by hgpu

Performance Optimization of GPU ELF-Codes

Fausto Artico

Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, PTX, Tesla C2070, Thesis

May 15, 2014 by hgpu

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Christoph Kessler, Usman Dastgeer, Lu Li

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Review, Tesla C2050

May 15, 2014 by hgpu

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Jakub Kurzak, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680

May 14, 2014 by hgpu

Evaluating the Power of GPU Acceleration for IDW Interpolation Algorithm

Gang Mei

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Tags: Algorithms, Computer science, CUDA, Geoscience, nVidia, nVidia GeForce GT 640

May 14, 2014 by hgpu

Build and Travel KD-Tree with CUDA

Meng Zhou

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Tags: 3D Graphics and Realism, Computer science, CUDA, KD-tree, nVidia, nVidia GeForce GTX 780 Ti, Package, Raytracing

May 14, 2014 by hgpu

Cluster-Level Tuning of a Shallow Water Equation Solver on the Intel MIC Architecture

Andrey Vladimirov, Cliff Addison

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Tags: cfd, Fluid dynamics, intel mic, Intel Xeon Phi, MPI, OpenMP

May 13, 2014 by Andrey Vladimirov

Impact of Modern OpenGL on FPS

Jan Cejka

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 580, nVidia Quadro 6000, OpenGL, Performance, Rendering

May 13, 2014 by hgpu

Deriving Shape Grammars on the GPU

Mark Dokter

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, OpenGL, Performance

May 13, 2014 by hgpu

K-Means on GPU: A Review

Vidya Dhamdhere, Rahul G. Ghudji

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, Review

May 13, 2014 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

A Straightforward Preprocessing Approach for Accelerating Convex Hull Computations on the GPU

Real-time Image Processing on Low Cost Embedded Computers

Parallelization of Shape Diameter Function Computation using OpenCL

Performance Optimization of GPU ELF-Codes

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Preliminary results of autotuning GEMM kernels for the NVIDIA Kepler architecture-GeForce GTX 680

Evaluating the Power of GPU Acceleration for IDW Interpolation Algorithm

Build and Travel KD-Tree with CUDA

Cluster-Level Tuning of a Shallow Water Equation Solver on the Intel MIC Architecture

Impact of Modern OpenGL on FPS

Deriving Shape Grammars on the GPU

K-Means on GPU: A Review

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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