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Performance study of mapping irregular computations on GPUs

Steven Solomon, Parimala Thulasiraman

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, Presentation

March 6, 2011 by hgpu

Redesigning combustion modeling algorithms for the Graphics Processing Unit (GPU): Chemical kinetic rate evaluation and ordinary differential equation integration

Yu Shi, William H. Green, Hsi-Wu Wong, Oluwayemisi O. Oluwole

Tags: Chemistry, Computational modelling, CUDA, nVidia, nVidia GeForce GTX 260, Tesla C2050

March 4, 2011 by hgpu

Accelerating CUDA Graph Algorithms at Maximum Warp

Sungpack Hong, Sang Kyun Kim, Tayo Oguntebi, Kunle Olukotun

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, Package, Performance, Programming techniques

February 27, 2011 by hgpu

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

Dana A. Jacobsen, Julien C. Thibault, Inanc Senocak

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Tags: CUDA, Fluid dynamics, GPU cluster, MPI, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260, Tesla C1060, Tesla C870, Tesla S1070, Tesla S870

February 24, 2011 by hgpu

GPU Accelerated Particle System for Triangulated Surface Meshes

Brad Peterson, Manasi Datar, Mary Hall, Ross Whitaker

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Particle simulation, Triangular meshes

February 17, 2011 by hgpu

Takagi Factorization on GPU using CUDA

Gagandeep S. Sachdev, Vishay Vanjani and Mary W. Hall

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Tags: Computer science, CUDA, Factorization, Matrix decomposition, nVidia, nVidia GeForce GTX 260

February 17, 2011 by hgpu

Visualising spins and clusters in regular and small-world Ising models with GPUs

A. Leist, D.P. Playne and K.A. Hawick

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Tags: CUDA, Ising model, nVidia, nVidia GeForce GTX 260, OpenGL, Physics, Visualization

February 13, 2011 by hgpu

Data-Parallelism and GPUs for Lattice Gas Fluid Simulations

M.G.B. Johnson, D.P. Playne and K.A. Hawick

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Tags: Cellular automata, Computer science, CUDA, Fluid simulation, nVidia, nVidia GeForce GT 220, nVidia GeForce GTX 210, nVidia GeForce GTX 260, nVidia GeForce GTX 295

February 13, 2011 by hgpu

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

D.P. Playne, K.A. Hawick

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Tags: Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Partial differential equations, PDEs

February 13, 2011 by hgpu

Interactive visualisation of spins and clusters in regular and small-world Ising models with CUDA on GPUs

A. Leist, D.P. Playne and K.A. Hawick

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Tags: CUDA, Ising model, nVidia, nVidia GeForce GTX 260, OpenGL, Physics, Visualization

February 13, 2011 by hgpu

3D Registration Based on Normalized Mutual Information: Performance of CPU vs. GPU Implementation

Florian Jung, Stefan Wesarg

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Tags: CUDA, Image processing, Image registration, Medicine, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285

February 3, 2011 by hgpu

Asynchronous Communication Schemes for Finite Difference Methods on Multiple GPUs

Daniel P. Playne, Kenneth A. Hawick

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Tags: Computer science, CUDA, Finite difference, GPU cluster, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 295

January 30, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Performance study of mapping irregular computations on GPUs

Redesigning combustion modeling algorithms for the Graphics Processing Unit (GPU): Chemical kinetic rate evaluation and ordinary differential equation integration

Accelerating CUDA Graph Algorithms at Maximum Warp

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

GPU Accelerated Particle System for Triangulated Surface Meshes

Takagi Factorization on GPU using CUDA

Visualising spins and clusters in regular and small-world Ising models with GPUs

Data-Parallelism and GPUs for Lattice Gas Fluid Simulations

Comparison of GPU Architectures for Asynchronous Communication with Finite-Differencing Applications

Interactive visualisation of spins and clusters in regular and small-world Ising models with CUDA on GPUs

3D Registration Based on Normalized Mutual Information: Performance of CPU vs. GPU Implementation

Asynchronous Communication Schemes for Finite Difference Methods on Multiple GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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