high performance computing on graphics processing units: hgpu.org

hgpu.org » Algorithms

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

Eike Hermann Muller, Robert Scheichl, Benson Muite, Eero Vainikko

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Numerical Analysis, nVidia, Partial differential equations, PDEs, Tesla K20, Tesla M2090

February 17, 2014 by hgpu

Interactive Design Exploration for Constrained Meshes

Bailin Deng, Sofien Bouaziz, Mario Deuss, Alexandre Kaspar, Yuliy Schwartzburg, Mark Pauly

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Tags: Algorithms, CAD, Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GTX 580

February 17, 2014 by hgpu

Efficient pseudo-random number generation for monte-carlo simulations using graphic processors

Siddhant Mohanty, A K Mohanty, F Carminati

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Tags: Algorithms, Computer science, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, OpenCL, Pseudo-random number generators

February 17, 2014 by hgpu

Resolution of Linear Algebra for the Discrete Logarithm Problem using GPU and Multi-core Architectures

Hamza Jeljeli

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 680, OpenMPI, Security, Tesla M2050

February 17, 2014 by hgpu

Work-Efficient Parallel GPU Methods for Single-Source Shortest Paths

Andrew Davidson, Sean Baxter, Michael Garland, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 680, Package

February 15, 2014 by hgpu

Computation of Galois field expressions for quaternary logic functions on GPUs

Dusan B. Gajic

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Tags: Algorithms, ATI, ATI Radeon HD 6750, Computer science, FFT, nVidia, nVidia GeForce GTX 560 Ti, OpenCL

February 15, 2014 by hgpu

Increasing precision of uniform pseudorandom number generators

Vadim Demchik, Alexey Gulov

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Tags: Algorithms, Computer science, Extended precision, Mathematical Software, Pseudo-random number generators, Security

February 12, 2014 by hgpu

Designing Bit-Reproducible Portable High-Performance Applications

Andrea Arteaga, Oliver Fuhrer, Torsten Hoefler

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Portability, Tesla K20

February 12, 2014 by hgpu

Minerals detection for hyperspectral images using adapted linear unmixing: LinMin

Schmidt Frederic, Legendre Maxime, Le Mouelic Stephane

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Tags: Algorithms, Astrophysics, CUDA, Earth and Planetary Astrophysics, nVidia, Tesla C2050

February 12, 2014 by hgpu

Exploiting GPU Parallelism to Optimize Real-World Problems

Hasan Furhad, Fahmida Ahmed, Faisal Faruque, Iqbal Hasan Sarker

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Optimization

February 11, 2014 by hgpu

Fast 2-D Ultrasound Strain Imaging: The Benefits of Using a GPU

Tim Idzenga, Evghenii Gaburov, Willem Vermin, Jan Menssen, Chris L. de Korte

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Tags: Algorithms, CUDA, Image processing, nVidia, OpenMP, Package, Tesla K20, Ultrasound

February 8, 2014 by hgpu

Depth Map Based Superresolution Method in 3D Reconstruction

Gabriel Bernardino

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Tesla C1060, Thesis

February 5, 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

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

Interactive Design Exploration for Constrained Meshes

Efficient pseudo-random number generation for monte-carlo simulations using graphic processors

Resolution of Linear Algebra for the Discrete Logarithm Problem using GPU and Multi-core Architectures

Work-Efficient Parallel GPU Methods for Single-Source Shortest Paths

Computation of Galois field expressions for quaternary logic functions on GPUs

Increasing precision of uniform pseudorandom number generators

Designing Bit-Reproducible Portable High-Performance Applications

Minerals detection for hyperspectral images using adapted linear unmixing: LinMin

Exploiting GPU Parallelism to Optimize Real-World Problems

Fast 2-D Ultrasound Strain Imaging: The Benefits of Using a GPU

Depth Map Based Superresolution Method in 3D Reconstruction

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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