high performance computing on graphics processing units: hgpu.org

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Parallel Computing of Discrete Element Method on GPU

Teruyoshi Washizawa, Yasuhiro Nakahara

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Tags: Computational Engineering, Computer science, CUDA, nVidia, OpenCL, Tesla C2050

January 11, 2013 by hgpu

Parallel Algorithms for Constructing Data Structures for Fast Multipole Methods

Qi Hu, Nail A. Gumerov, Ramani Duraiswami

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, Heterogeneous systems, Mathematical Software, nVidia, nVidia GeForce GTX 480

January 11, 2013 by hgpu

On Graphs, GPUs, and Blind Dating: A Workload to Processor Matchmaking Quest

Abdullah Gharaibeh, Lauro Beltrao Costa, Elizeu Santos-Neto, Matei Ripeanu

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2075

January 10, 2013 by hgpu

GPU-Based Super-union for Minkowski Sum

Yuen- Shan Leung, Charlie C. L. Wang, Yong Chen

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Voxelization

January 10, 2013 by hgpu

Multi-Platform LU-Decomposition Solution in OpenCL

Ehsan Nasiri, Rafat Rashid, Saurabh Verma

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Computer science, FPGA, Linear Algebra, OpenCL

January 10, 2013 by hgpu

An implementation for quad-tree based solid object coloring using CUDA

Baha Sen, Caner Ozcan, Nesrin Aydin Atasoy

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, nVidia Quadro FX 2000

January 9, 2013 by hgpu

Low cost approach to real-time vehicle to vehicle communication using parallel CPU and GPU processing

Goh Chia Chieh, Dino Isa

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 M GTX, Vehicular traffic

January 8, 2013 by hgpu

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Dominik Grewe, Zheng Wang, Michael F.P. O'Boyle

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Programming Languages

January 8, 2013 by hgpu

Efficient Weighted Histogramming on GPUs with CUDA

Mo Xu, Ningyi Xu, Chunshui Zhao, Feng-Hsiung Hsu

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Tags: Computer science, CUDA, Data mining, Machine learning, nVidia, nVidia GeForce GTX 580

January 8, 2013 by hgpu

Distributed Massive Model Rendering

Revanth N R, P. J. Narayanan

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia Quadro FX 3700 M, Rendering, Tesla C2050, Tesla C2070, Tesla S1070

January 8, 2013 by hgpu

CUDA based iterative methods for linear systems

Bogdan Oancea

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 7, 2013 by hgpu

Performance comparison of gauss-Jordan elimination method using OpenMP and CUDA

Baha Sen, Nesrin Aydin Atasoy, Caner Ozcan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, OpenMP, Performance, Programming techniques

January 7, 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

Applications

Parallel Computing of Discrete Element Method on GPU

Parallel Algorithms for Constructing Data Structures for Fast Multipole Methods

On Graphs, GPUs, and Blind Dating: A Workload to Processor Matchmaking Quest

GPU-Based Super-union for Minkowski Sum

Multi-Platform LU-Decomposition Solution in OpenCL

An implementation for quad-tree based solid object coloring using CUDA

Low cost approach to real-time vehicle to vehicle communication using parallel CPU and GPU processing

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Efficient Weighted Histogramming on GPUs with CUDA

Distributed Massive Model Rendering

CUDA based iterative methods for linear systems

Performance comparison of gauss-Jordan elimination method using OpenMP and CUDA

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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