high performance computing on graphics processing units: hgpu.org

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Fast Feature Selection in a GPU Cluster Using the Delta Test

Alberto Guillen, M. Isabel Garcia Arenas, Mark van Heeswijk, Dusan Sovilj, Amaury Lendasse, Luis Javier Herrera, Hector Pomares, Ignacio Rojas

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Nearest neighbour, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GTX, nVidia GeForce GTS 450

February 25, 2014 by hgpu

WPA/WPA2 Password Security Testing using Graphics Processing Units

Sorin Andrei Visan

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GT 610 M, Security

February 23, 2014 by hgpu

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

Eike Hermann Muller, Robert Scheichl, Benson Muite, Eero Vainikko

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Numerical Analysis, nVidia, Partial differential equations, PDEs, Tesla K20, Tesla M2090

February 17, 2014 by hgpu

Fast American Basket Option Pricing on a multi-GPU Cluster

Michael Benguigui, Francoise Baude

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Tags: Finance, GPU cluster, Machine learning, nVidia, OpenCL, Option pricing, Tesla M2050, Tesla M2075, Tesla S1070

February 17, 2014 by hgpu

GROMACS on Hybrid CPU-GPU and CPU-MIC Clusters: Preliminary Porting Experiences, Results and Next Steps

Sadaf Alam, Ugo Varetto

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Tags: Computer science, CUDA, GPU cluster, Hybrid computing, Intel Xeon Phi, MPI, nVidia, OpenCL, Tesla K20

February 12, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Vivek K. Pallipuram

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Performance, Tesla K20, Tesla M2075, Thesis

February 11, 2014 by hgpu

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

Yongpeng Zhang, Frank Mueller

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

February 5, 2014 by hgpu

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

Farouk Mansouri, Sylvain Huet, Vincent Fristot, Dominique Houzet

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Tags: Computer science, CUDA, DSP, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia Quadro 4000, Signal processing

February 2, 2014 by hgpu

A QUDA-branch to compute disconnected diagrams in GPUs

Constantia Alexandrou, Kyriacos Hadjiyiannakou, Giannis Koutsou, Alexei Strelchenko, Alejandro Vaquero

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Monte Carlo simulation, MPI, nVidia, Physics, QCD, Tesla M2070

January 30, 2014 by hgpu

A Lattice Boltzmann Method Simulator for Microfluidics on GPU Cluster

Luiz Otavio S. Ferreira, Lucas Monteiro Volpe

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 580, Visualization

January 19, 2014 by hgpu

Resource Centered Computing delivering high parallel performance

Jens Gustedt, Stephane Vialle, Patrick Mercier

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Tags: Computer science, CUBLAS, CUDA, GPU cluster, Hierarchical clustering, MPI, nVidia, nVidia GeForce GTX 580

December 22, 2013 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

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high performance computing on graphics processing units: hgpu.org

Fast Feature Selection in a GPU Cluster Using the Delta Test

WPA/WPA2 Password Security Testing using Graphics Processing Units

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

Fast American Basket Option Pricing on a multi-GPU Cluster

GROMACS on Hybrid CPU-GPU and CPU-MIC Clusters: Preliminary Porting Experiences, Results and Next Steps

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

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

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

A QUDA-branch to compute disconnected diagrams in GPUs

A Lattice Boltzmann Method Simulator for Microfluidics on GPU Cluster

Resource Centered Computing delivering high parallel performance

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)