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Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

Jan Verschelde, Xiangcheng Yu

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Tags: Algorithms, Computer science, CUDA, Extended precision, Linear Algebra, Mathematical Software, Numerical Analysis, nVidia, Package, Tesla K20

January 28, 2015 by hgpu

GPU Programming – Speeding Up the 3D Surface Generator VESTA

B. R. Schlei

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Tags: Computed tomography, Computer science, CT, CUDA, Graphics, nVidia, nVidia GeForce GTX 750 Ti

January 28, 2015 by hgpu

On Longest Repeat Queries Using GPU

Yun Tian, Bojian Xu

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Tags: Biology, Computational biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 660 Ti

January 28, 2015 by hgpu

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Blesson Varghese

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Tags: Computational Engineering, Computer science, CUDA, Finance, Intel Xeon Phi, nVidia, Performance, Tesla C2075

January 28, 2015 by hgpu

Adjoint Lattice Boltzmann for Topology Optimization on multi-GPU architecture

Lukasz Laniewski-Wollk, Jacek Rokicki

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla M2090

January 26, 2015 by hgpu

A High Performance Framework for Coupled Urban Microclimate Models

Matthew C. Overby

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Tags: CUDA, Earth and Space Sciences, nVidia, nVidia GeForce GTX 690, Tesla S2050, Thesis, Visualization

January 26, 2015 by hgpu

GPU computing architecture for irregular parallelism

Wilson Wai Lun Fung

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Thesis

January 26, 2015 by hgpu

Performance Analysis of Join Algorithms on GPUs

Ran Rui, Hao Li, Yi-Cheng Tu

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Tags: Algorithms, Computer science, CUDA, Databases, Join, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, Performance

January 26, 2015 by hgpu

Real-time physically cloth simulation with CUDA

Li Huaming, Kang Baosheng

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, OpenGL, Rendering

January 23, 2015 by hgpu

Revisit Long Short-Term Memory: An Optimization Perspective

Qi Lyu, Jun Zhu

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Tags: Computer science, CUDA, Machine learning, MapReduce, Neural networks, nVidia, nVidia GeForce GTX 770

January 23, 2015 by hgpu

Gunrock: A High-Performance Graph Processing Library on the GPU

Yangzihao Wang, Andrew Davidson, Yuechao Pan, Yuduo Wu, Andy Riffel, John D. Owens

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 23, 2015 by hgpu

A Novel Implementation of QuickHull Algorithm on the GPU

Jiayin Zhang, Gang Mei, Nengxiong Xu, Kunyang Zhao

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Tags: Computational Geometry, Computer science, CUDA, Graphics, nVidia, Tesla K20

January 21, 2015 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

Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

GPU Programming – Speeding Up the 3D Surface Generator VESTA

On Longest Repeat Queries Using GPU

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Adjoint Lattice Boltzmann for Topology Optimization on multi-GPU architecture

A High Performance Framework for Coupled Urban Microclimate Models

GPU computing architecture for irregular parallelism

Performance Analysis of Join Algorithms on GPUs

Real-time physically cloth simulation with CUDA

Revisit Long Short-Term Memory: An Optimization Perspective

Gunrock: A High-Performance Graph Processing Library on the GPU

A Novel Implementation of QuickHull Algorithm on the GPU

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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