high performance computing on graphics processing units: hgpu.org

hgpu.org » GPU cluster

Multiscale Hemodynamics Using GPU Clusters

Mauro Bisson, Massimo Bernaschi, Simone Melchionna, Sauro Succi, Efthimios Kaxiras

View

Download (PDF)

Tags: Biology, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, Medicine, nVidia, Tesla C1060

February 17, 2012 by hgpu

Scalability of Self-organizing Maps on a GPU cluster using OpenCL and CUDA

Sabine McConnell, Robert Sturgeon, Gregory Henry, Andrew Mayne, Richard Hurley

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Data mining, GPU cluster, nVidia, nVidia GeForce GT 220, OpenCL, Self-organizing map, Tesla S1070

February 11, 2012 by hgpu

Implementing Molecular Dynamics on Hybrid High Performance Computers – Particle-Particle Particle-Mesh

W. Michael Brown, Axel Kohlmeyer, Steven J. Plimpton, Arnold N. Tharrington

View

Download (PDF)

Source codes

Tags: Algorithms, Chemistry, CUDA, Electrostatics, GPU cluster, Heterogeneous systems, Molecular dynamics, nVidia, OpenCL, OpenMPI, Package, Physics, Tesla M2070

February 10, 2012 by hgpu

Auto-Generation and Auto-Tuning of 3D Stencil Codes on GPU Clusters

Yongpeng Zhang, Frank Mueller

View

Download (PDF)

Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Nearest neighbour, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Tesla C1060, Tesla C2050

February 8, 2012 by hgpu

How well do STARLAB and NBODY compare? II: Hardware and accuracy

P. Anders, H. Baumgardt, E. Gaburov, S. Portegies Zwart

View

Download (PDF)

Tags: Algorithms, Astrophysics, Cosmology and Extragalactic Astrophysics, Galaxy Astrophysics, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce 9800 GX2

January 30, 2012 by hgpu

Automatic Code Generation and Adaptive Grid Scheduling for GPU Cluster Computing

Xuyuan Jin

View

Download (PDF)

Tags: Cluster computing, Code generation, Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 570

January 21, 2012 by hgpu

Combining approximate inference methods for efficient learning on large computer clusters

Zhenwen Dai, Jacquelyn A. Shelton, Jorg Bornschein, Abdul Saboor Sheikh, Jorg Lucke

View

Download (PDF)

Tags: Algorithms, Computational Complexity, Computer science, GPU cluster, Machine learning, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Python

January 19, 2012 by hgpu

CPU/GPU computing for long-wave radiation physics on large GPU clusters

Fengshun Lu, Junqiang Song, Xiaoqun Cao, Xiaoqian Zhu

View

Download (PDF)

Tags: CUDA, Earth and Space Sciences, Geoscience, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenMP, Tesla M2050

January 17, 2012 by hgpu

Graphics Processor Clusters for High Speed Backpropagation

Daniel P. Campbell, Daniel A. Cook

View

Download (PDF)

Tags: CUDA, GPU cluster, nVidia, nVidia GeForce GTX 480, Optimization, Signal processing, Tesla C2050

January 14, 2012 by hgpu

DFG Implementation on Multi GPU Cluster with Computation-Communication Overlap

Sylvain Huet, Vincent Boulos, Vincent Fristot, Luc Salvo

View

Download (PDF)

Tags: Algorithms, CUDA, DSP, GPU cluster, nVidia, nVidia GeForce GTX 285, Signal processing

January 13, 2012 by hgpu

Petaflop biofluidics simulations on a two million-core system

Massimo Bernaschi, Satoshi Matsuoka, Mauro Bisson, Massimiliano Fatica, Toshio Endo, Simone Melchionna

View

Download (PDF)

Tags: Algorithms, Biology, CUDA, GPU cluster, Medicine, nVidia, Optimization, Tesla M2050

January 11, 2012 by hgpu

Multiphase Fluid Simulations on a Multiple GPGPU PC Using Unsplit Time Integration VSIAM3

Akio Ikebata, Yoshihiko Muraoka, Feng Xiao

View

Download (PDF)

Tags: Fluid dynamics, Fluid simulation, GPU cluster, nVidia, nVidia GeForce GTX 295, OpenCL

January 7, 2012 by hgpu

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Multiscale Hemodynamics Using GPU Clusters

Scalability of Self-organizing Maps on a GPU cluster using OpenCL and CUDA

Implementing Molecular Dynamics on Hybrid High Performance Computers – Particle-Particle Particle-Mesh

Auto-Generation and Auto-Tuning of 3D Stencil Codes on GPU Clusters

How well do STARLAB and NBODY compare? II: Hardware and accuracy

Automatic Code Generation and Adaptive Grid Scheduling for GPU Cluster Computing

Combining approximate inference methods for efficient learning on large computer clusters

CPU/GPU computing for long-wave radiation physics on large GPU clusters

Graphics Processor Clusters for High Speed Backpropagation

DFG Implementation on Multi GPU Cluster with Computation-Communication Overlap

Petaflop biofluidics simulations on a two million-core system

Multiphase Fluid Simulations on a Multiple GPGPU PC Using Unsplit Time Integration VSIAM3

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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

Most viewed papers (last 30 days)