high performance computing on graphics processing units: hgpu.org

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MPI-ACC: An Integrated and Extensible Approach to Data Movement in Accelerator-Based Systems

Ashwin M. Aji, James Dinan, Darius Buntinas, Pavan Balaji, Wu-chun Feng, Keith R. Bisset, Rajeev Thakur

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Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, Tesla C2050

June 1, 2012 by hgpu

Large-scale Nanostructure Simulations from X-ray Scattering Data On Graphics Processor Clusters

Abhinav Sarje, Jack Pien, Xiaoye S. Li, Elaine Chan, Slim Chourou, Alexander Hexemer, Arthur Scholz and Edward Kramer

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Tags: Algorithms, CUDA, GPU cluster, Monte Carlo simulation, MPI, nVidia, Optimization, Physics, Tesla C2050, Tesla M2090

May 30, 2012 by hgpu

Massively Parallel Neural Encoding and Decoding of Visual Stimuli

Aurel A. Lazar, Yiyin Zhou

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Neural networks, nVidia, Tesla M2050

May 29, 2012 by hgpu

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

VCV.Rao, Nisha Agrawa, Samrit Maity

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Tags: AMD FirePro V5900, AMD FirePro V7900, AMD FireStream 9350, ATI, Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, OpenCL, Partial differential equations, PDEs, Tesla C2060

May 19, 2012 by hgpu

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

Alan Humphrey, Qingyu Meng, Martin Berzins, Todd Harman

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Tags: CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, MPI, nVidia, Partial differential equations, Pthreads, Task scheduling, Tesla M2090

May 11, 2012 by hgpu

Solving incompressible two-phase flows on multi-GPU clusters

Peter Zaspel, Michael Griebel

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Tags: CUDA, Finite difference, Fluid dynamics, GPU cluster, Navier-Stokes equations, nVidia, Tesla C2050, Tesla S1070

April 16, 2012 by hgpu

A Scalable Framework for Heterogeneous GPU-Based Clusters

Fengguang Song, Jack Dongarra, Stanimire Tomov

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Tags: Algorithms, Computer science, CUDA, Factorization, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, Tesla M2070

April 7, 2012 by hgpu

Multi-GPU parallelization of a 3D Bayesian CT algorithm and its application on real foam reconstruction with incomplete data set

Nicolas Gac, Alexandre Vabre, Ali Mohammad Djafari

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Tags: Algorithms, Bayesian, Computed tomography, CT, CUDA, GPU cluster, Image reconstruction, Medicine, nVidia, Tesla C1060, Tomography

March 31, 2012 by hgpu

Towards user transparent parallel multimedia computing on GPU-clusters

Ben van Werkhoven, Jason Maassen, Frank J. Seinstra

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Tags: Computer science, CUDA, GPU cluster, nVidia, Performance, Tesla M1060

March 18, 2012 by hgpu

GPU-Accelerated Large-Eddy Simulation of Turbulent Channel Flows

Rey DeLeon, Inanc Senocak

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Tags: CUDA, Fluid dynamics, GPU cluster, Numerical simulation, nVidia

March 10, 2012 by hgpu

Scalable framework for mapping streaming applications onto multi-GPU systems

Huynh Phung Huynh, Andrei Hagiescu, Weng-Fai Wong, Rick Siow Mong Goh

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Tags: Algorithms, Code generation, Computer science, CUDA, GPU cluster, nVidia, Tesla C2070

March 8, 2012 by hgpu

Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

Xiong QinGang, Li Bo, Xu Ji, Fang XiaoJian, Wang XiaoWei, Wang LiMin, He XianFeng, Ge Wei

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Tags: Algorithms, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, Numerical simulation, nVidia, Tesla C2050

February 22, 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

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high performance computing on graphics processing units: hgpu.org

MPI-ACC: An Integrated and Extensible Approach to Data Movement in Accelerator-Based Systems

Large-scale Nanostructure Simulations from X-ray Scattering Data On Graphics Processor Clusters

Massively Parallel Neural Encoding and Decoding of Visual Stimuli

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

Radiation Modeling Using the Uintah Heterogeneous CPU/GPU Runtime System

Solving incompressible two-phase flows on multi-GPU clusters

A Scalable Framework for Heterogeneous GPU-Based Clusters

Multi-GPU parallelization of a 3D Bayesian CT algorithm and its application on real foam reconstruction with incomplete data set

Towards user transparent parallel multimedia computing on GPU-clusters

GPU-Accelerated Large-Eddy Simulation of Turbulent Channel Flows

Scalable framework for mapping streaming applications onto multi-GPU systems

Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

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

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