high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

AES finalists implementation for GPU and multi-core CPU based on OpenCL

Xingliang Wang, Xiaochao Li, Mei Zou, Jun Zhou

Tags: AES, Benchmarking, Computer science, CUDA, nVidia, OpenCL, Security

August 8, 2011 by hgpu

The distributed diagonal force decomposition method for parallelizing molecular dynamics simulations

Urban Borstnik, Benjamin T. Miller, Bernard R. Brooks, Dusanka Janezic

Tags: Algorithms, Chemistry, Computational chemistry, Molecular dynamics, Performance

August 8, 2011 by hgpu

DC Power Flow Based Contingency Analysis Using Graphics Processing Units (thesis)

Anupam Gopal

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Tags: Cg, Computer science, nVidia, nVidia GeForce 7800 GTX, OpenGL, Power Systems Simulation, Thesis

August 8, 2011 by hgpu

DC Power Flow Based Contingency Analysis Using Graphics Processing Units

Anupam Gopal, Dagmar Niebur, Suresh Venkatasubramanian

Tags: Cg, Computer science, nVidia, nVidia GeForce 7800 GTX, OpenGL, Power Systems Simulation

August 8, 2011 by hgpu

GPU implementation of a Helmholtz Krylov Solver preconditioned by a shifted Laplace multigrid method

H. Knibbe, C. W. Oosterlee, C. Vuik

Tags: CUDA, Finite difference, Mathematics, nVidia

August 8, 2011 by hgpu

Structural, dynamic, and electrostatic properties of fully hydrated DMPC bilayers from molecular dynamics simulations accelerated with graphical processing units (GPUs)

Narayan Ganesan, Brad A. Bauer, Timothy R. Lucas, Sandeep Patel, Michela Taufer

Tags: Algorithms, Chemistry, Computational chemistry, Electrostatic potential, Electrostatics, Molecular dynamics

August 8, 2011 by hgpu

On the GPGPU parallelization issues of finite element approximate inverse preconditioning

C. K. Filelis-Papadopoulos, G. A. Gravvanis, P. I. Matskanidis, K. M. Giannoutakis

Tags: Algorithms, Computer science, CUDA, Finite element method, nVidia, Sparse linear iterative solvers

August 8, 2011 by hgpu

PUGACE, a cellular Evolutionary Algorithm framework on GPUs

Nicolas Soca, Jose Luis Blengio, Martin Pedemonte, Pablo Ezzatti

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Metaheuristics, nVidia, nVidia GeForce 9800 GTX, Optimization

August 7, 2011 by hgpu

A simple and flexible volume rendering framework for graphics-hardware-based raycasting

Simon Stegmaier, Magnus Strengert, Thomas Klein, Thomas Ertl

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Source codes

Tags: 3D Graphics and Realism, Benchmarking, Computer science, Image generation, nVidia, nVidia GeForce 6800 GT, OpenGL, Package, Raytracing, Rendering

August 7, 2011 by hgpu

A convex formulation for color image segmentation in the context of passive emitter localization

Marek Schikora, Miriam Hage, Eicke Ruthotto, Klaus Wild

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 280

August 7, 2011 by hgpu

A pure vision-based approach to topological SLAM

Wen Lik Dennis Lui, Ray Jarvis

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Optical flow, Wavelet

August 7, 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

AES finalists implementation for GPU and multi-core CPU based on OpenCL

The distributed diagonal force decomposition method for parallelizing molecular dynamics simulations

DC Power Flow Based Contingency Analysis Using Graphics Processing Units (thesis)

DC Power Flow Based Contingency Analysis Using Graphics Processing Units

GPU implementation of a Helmholtz Krylov Solver preconditioned by a shifted Laplace multigrid method

Structural, dynamic, and electrostatic properties of fully hydrated DMPC bilayers from molecular dynamics simulations accelerated with graphical processing units (GPUs)

On the GPGPU parallelization issues of finite element approximate inverse preconditioning

PUGACE, a cellular Evolutionary Algorithm framework on GPUs

A simple and flexible volume rendering framework for graphics-hardware-based raycasting

A convex formulation for color image segmentation in the context of passive emitter localization

A pure vision-based approach to topological SLAM

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)