Applications

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Hypercubic Storage Layout and Transforms in Arbitrary Dimensions using GPUs and CUDA

K.A. Hawick and D.P. Playne

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 295, Storage system

February 14, 2011 by hgpu

Comparing Intra- and Inter-Processor Parallelism on Multi-Core Cell Processors for Scientific Simulations

K.A. Hawick, A. Leist and D.P. Playne and M.J. Johnson

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Tags: Cell processor, Computer science, Playstation, Pseudo-random number generators

February 14, 2011 by hgpu

Biomolecular electrostatics using a fast multipole BEM on up to 512 GPUs and a billion unknowns

Rio Yokota, Jaydeep P. Bardhan, Matthew G. Knepley, L. A. Barba, Tsuyoshi Hamada

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Tags: Chemical Physics, Computational Physics, Computer science, CUDA, Electrostatics, Fast multipole method, Integral equations, nVidia, nVidia GeForce GTX 295, Package

February 14, 2011 by hgpu

An FPGA-based Torus Communication Network

Marcello Pivanti, Sebastiano Fabio Schifano, Hubert Simma

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Tags: FPGA, High Energy Physics - Lattice, Network communications, Networks, Physics

February 14, 2011 by hgpu

Speed and Portability issues for Random Number Generation on Graphical Processing Units with CUDA and other Processing Accelerators

K.A. Hawick, A. Leist, D.P. Playne, M.J. Johnson

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Tags: Cell processor, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 295, Pseudo-random number generators

February 13, 2011 by hgpu

Cluster and Fast-Update Simulations of Regular and Rewired Lattice Ising Models Using CUDA and Graphical Processing Units

K.A. Hawick, A.Leist and D.P.Playne

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Tags: CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Physics

February 13, 2011 by hgpu

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

K.A. Hawick and D.P. Playne

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Tags: Code generation, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 295, Partial differential equations, PDEs

February 13, 2011 by hgpu

Visualising spins and clusters in regular and small-world Ising models with GPUs

A. Leist, D.P. Playne and K.A. Hawick

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Tags: CUDA, Ising model, nVidia, nVidia GeForce GTX 260, OpenGL, Physics, Visualization

February 13, 2011 by hgpu

Data-Parallelism and GPUs for Lattice Gas Fluid Simulations

M.G.B. Johnson, D.P. Playne and K.A. Hawick

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Tags: Cellular automata, Computer science, CUDA, Fluid simulation, nVidia, nVidia GeForce GT 220, nVidia GeForce GTX 210, nVidia GeForce GTX 260, nVidia GeForce GTX 295

February 13, 2011 by hgpu

GPU-based Multi-Volume Rendering of Complex Data in Neuroscience and Neurosurgery

Johanna Beyer

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Tags: Computed tomography, Computer science, CT, CUDA, Medicine, Neuroscience, nVidia, nVidia GeForce GTX 280, Rendering, Visualization

February 13, 2011 by hgpu

Interactive visualisation of spins and clusters in regular and small-world Ising models with CUDA on GPUs

A. Leist, D.P. Playne and K.A. Hawick

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Tags: CUDA, Ising model, nVidia, nVidia GeForce GTX 260, OpenGL, Physics, Visualization

February 13, 2011 by hgpu

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

D.P. Playne, K.A. Hawick

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Tags: Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Partial differential equations, PDEs

February 13, 2011 by hgpu

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

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

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high performance computing on graphics processing units: hgpu.org

Applications

Hypercubic Storage Layout and Transforms in Arbitrary Dimensions using GPUs and CUDA

Comparing Intra- and Inter-Processor Parallelism on Multi-Core Cell Processors for Scientific Simulations

Biomolecular electrostatics using a fast multipole BEM on up to 512 GPUs and a billion unknowns

An FPGA-based Torus Communication Network

Speed and Portability issues for Random Number Generation on Graphical Processing Units with CUDA and other Processing Accelerators

Cluster and Fast-Update Simulations of Regular and Rewired Lattice Ising Models Using CUDA and Graphical Processing Units

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

Visualising spins and clusters in regular and small-world Ising models with GPUs

Data-Parallelism and GPUs for Lattice Gas Fluid Simulations

GPU-based Multi-Volume Rendering of Complex Data in Neuroscience and Neurosurgery

Interactive visualisation of spins and clusters in regular and small-world Ising models with CUDA on GPUs

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

Recent source codes

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

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

Most viewed papers (last 30 days)