high performance computing on graphics processing units: hgpu.org

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Efficient implementation of the overlap operator on multi-GPUs

Andrei Alexandru, Michael Lujan, Craig Pelissier, Ben Gamari, Frank X. Lee

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Tags: GPU cluster, High Energy Physics - Lattice, MPI, nVidia, Performance, Physics, Tesla M2070

June 27, 2011 by hgpu

Performance evaluation of the multi-device OpenCL FDTD solver

Tomasz P. Stefanski, Nicolas Chavannes, Niels Kuster

Tags: Electrodynamics, FDTD, Finite-difference time-domain, GPU cluster, OpenCL

June 21, 2011 by hgpu

Accelerating Viola-Jones Face Detection to FPGA-Level Using GPUs

Daniel Hefenbrock, Jason Oberg, Nhat Tan Nguyen Thanh, Ryan Kastner, Scott B. Baden

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Tags: Computer science, Computer vision, CUDA, FPGA, GPU cluster, Image recognition, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 295

June 15, 2011 by hgpu

Keynote address: Immersive exploration of large datasets

A. Kaufman

Tags: Computer science, Computer vision, GPU cluster, Rendering

June 15, 2011 by hgpu

A Tuned and Scalable Fast Multipole Method as a Preeminent Algorithm for Exascale Systems

Rio Yokota, Lorena Barba

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, GPU cluster, Heterogeneous systems, Numerical Analysis, nVidia, nVidia GeForce GTX 295, OpenMP

June 14, 2011 by hgpu

Parallelization of tau-leap coarse-grained Monte Carlo simulations on GPUs

Lifan Xu, Michela Taufer, Stuart Collins, Dionisios G. Vlachos

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Tags: Chemistry, CUDA, Data parallelism, GPU cluster, Monte Carlo simulation, nVidia, Physics, Tesla S1070

June 9, 2011 by hgpu

Dynamic load balancing on heterogeneous multicore/multiGPU systems

Alejandro Acosta, Robert Corujo, Vicente Blanco, Francisco Almeida

Tags: Computer science, GPU cluster, Heterogeneous systems, Performance, Task scheduling

June 8, 2011 by hgpu

Performance Analysis of the OP2 Framework on Many-core Architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall and P.H.J Kelly

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Tags: CUDA, Fluid dynamics, GPU cluster, nVidia, nVidia GeForce GTX 260, OpenMP, Package, Performance, Tesla C2050

June 5, 2011 by hgpu

A framework for parallel unstructured grid applications on GPUs

Mike Giles

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenCL, OpenMP, Package, PDEs, Presentation

June 5, 2011 by hgpu

QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators

Emmanuel Agullo, Cedric Augonnet, Jack Dongarra, Mathieu Faverge, Hatem Ltaief, Samuel Thibault, Stanimire Tomov

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Tags: Computer science, CUDA, Factorization, GPU cluster, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla S1070

June 5, 2011 by hgpu

Multiple-GPUs Algorithm for Lattice Boltzmann Method

Jifu Zhou, Chengwen Zhong, Jianfei Xie, Shiqun Yin

Tags: Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, OpenGL, Rendering

June 3, 2011 by hgpu

Modeling Rotor Wakes with a Hybrid OVERFLOW-Vortex Method on a GPU Cluster

Mark J. Stock, Adrin Gharakhani, Christopher P. Stone

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Tags: Fluid dynamics, Fluid simulation, GPU cluster, nVidia, nVidia GeForce GTX 275, Tesla S1070

June 3, 2011 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

Efficient implementation of the overlap operator on multi-GPUs

Performance evaluation of the multi-device OpenCL FDTD solver

Accelerating Viola-Jones Face Detection to FPGA-Level Using GPUs

Keynote address: Immersive exploration of large datasets

A Tuned and Scalable Fast Multipole Method as a Preeminent Algorithm for Exascale Systems

Parallelization of tau-leap coarse-grained Monte Carlo simulations on GPUs

Dynamic load balancing on heterogeneous multicore/multiGPU systems

Performance Analysis of the OP2 Framework on Many-core Architectures

A framework for parallel unstructured grid applications on GPUs

QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators

Multiple-GPUs Algorithm for Lattice Boltzmann Method

Modeling Rotor Wakes with a Hybrid OVERFLOW-Vortex Method on a GPU Cluster

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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