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Speed-Up Improvement Using Parallel Approach in Image Steganography

JyothiUpadhya K, U Dinesh Acharya, Hemalatha S

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Tags: Algorithms, Image processing, nVidia, nVidia GeForce GT 640, OpenCL

December 22, 2013 by hgpu

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

H. Khaled, R. El Gohary, N. L. Badr, H. M. Faheem

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 540 M, Sequence alignment, Smith-Waterman algorithm

December 22, 2013 by hgpu

GPU Accelerated Graph SLAM and Occupancy Voxel Based ICP For Encoder-Free Mobile Robots

Adrian Ratter, Claude Sammut, Matthew McGill

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 570

December 21, 2013 by hgpu

Parallel Compact Genetic Algorithm on CUDA-C Platform

Vuppuluri Sumati

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Genetic programming, nVidia

December 21, 2013 by hgpu

Design and Optimization of OpenFOAM-based CFD Applications for Modern Hybrid and Heterogeneous HPC Platforms

Amani AlOnazi

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Tags: Algorithms, Conjugate gradient solver, CUDA, Fluid dynamics, Heterogeneous systems, Laplace and Poisson equation, Linear Algebra, MPI, Numerical simulation, nVidia, Tesla C2050, Thesis

December 21, 2013 by hgpu

Pannotia: Understanding Irregular GPGPU Graph Applications

Shuai Che, Bradford M. Beckmann, Steven K. Reinhardt, Kevin Skadron

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Tags: Algorithms, ATI, ATI Radeon HD 7950, Computer science, OpenCL

December 20, 2013 by hgpu

Adapting the GA Approach to Solve Traveling Salesman Problems on CUDA Architecture

Ugur Cekmez, Mustafa Ozsiginan, Ozgur Koray Sahingoz

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, Path problems, Vehicular traffic

December 20, 2013 by hgpu

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Hristo Djidjev, Sunil Thulasidasan, Guillaume Chapuis, Rumen Andonov, Dominique Lavenier

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Tags: Algorithms, Bioinformatics, Biology, CUDA, GPU cluster, nVidia, Tesla C2090

December 18, 2013 by hgpu

A comparative analysis of the performance and deployment overhead of parallelized Finite Difference Time Domain (FDTD) algorithms on a selection of high performance multiprocessor computing systems

Robert Georg Ilgner

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Tags: Algorithms, CUDA, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, nVidia, nVidia GeForce GTX 480, Tesla C2070, Thesis

December 18, 2013 by hgpu

Data Structures for Task-based Priority Scheduling

Martin Wimmer, Daniel Cederman, Francesco Versaci, Jesper Larsson Traff, Philippas Tsigas

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Tags: Algorithms, Computer science, Intel Xeon Phi, Package, Task scheduling

December 17, 2013 by hgpu

OpenCL Accelerated Multi-GPU Cone-Beam Reconstruction

Marc Kaseberg, Steffen Melnik, Erwin Keeve

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Tags: Algorithms, ATI, ATI Radeon HD 5770, ATI Radeon HD 6970, Computed tomography, CT, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia Quadro 600, OpenCL, Tomography

December 17, 2013 by hgpu

Ray-Traced Collision Detection: Interpenetration Control and Multi-GPU Performance

Francois Lehericey, Valerie Gouranton, Bruno Arnaldi

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Tags: Algorithms, Collision detection, Computer science, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 660, OpenCL, Raytracing

December 16, 2013 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

Programming

Speed-Up Improvement Using Parallel Approach in Image Steganography

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

GPU Accelerated Graph SLAM and Occupancy Voxel Based ICP For Encoder-Free Mobile Robots

Parallel Compact Genetic Algorithm on CUDA-C Platform

Design and Optimization of OpenFOAM-based CFD Applications for Modern Hybrid and Heterogeneous HPC Platforms

Pannotia: Understanding Irregular GPGPU Graph Applications

Adapting the GA Approach to Solve Traveling Salesman Problems on CUDA Architecture

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

A comparative analysis of the performance and deployment overhead of parallelized Finite Difference Time Domain (FDTD) algorithms on a selection of high performance multiprocessor computing systems

Data Structures for Task-based Priority Scheduling

OpenCL Accelerated Multi-GPU Cone-Beam Reconstruction

Ray-Traced Collision Detection: Interpenetration Control and Multi-GPU Performance

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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