high performance computing on graphics processing units: hgpu.org

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Initial condition for efficient mapping of level set algorithms on many-core architectures

Gabor Janos Tornai, Gyorgy Cserey

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Tags: Differential equations, nVidia, nVidia GeForce GTX 780, OpenCL, Package, Partial differential equations, PDEs, Signal processing

March 14, 2014 by hgpu

Development of High-Performance Software Components for Emerging Architectures

Stefan Lemvig Glimberg, Allan Peter Engsig-Karup, Allan S. Nielsen, Bernd Dammann

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Tags: Computer science, CUDA, GPGPU, iterative methods, Mathematics, multigrid, Package, parallel computing, Partial differential equations, Software development

March 12, 2014 by apek

GPU Accelerated Discontinuous Galerkin Methods for Shallow Water Equations

R. Gandham, D. S. Medina, T. Warburton

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Tags: Algorithms, ATI, ATI Radeon HD 7970, CUDA, Differential equations, Mathematics, Numerical Analysis, nVidia, OCCA, OpenCL, Partial differential equations, PDEs, Tesla C2050, Tesla K20

March 10, 2014 by hgpu

A GPU Accelerated Aggregation Algebraic Multigrid Method

Rajesh Gandham, Ken Esler, Yongpeng Zhang

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Tags: Algorithms, CUDA, Mathematics, Numerical Analysis, nVidia, Partial differential equations, PDEs, Tesla M2090

March 10, 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

Optimizing Performance of Stencil Code with SPL Conqueror

Alexander Grebhahn, Norbert Siegmund, Sven Apel, Sebastian Kuckuk, Christian Schmitt, Harald Kostler

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Tags: Computer science, CUDA, Differential equations, Finite difference, Image processing, nVidia, OpenCL, Package, Partial differential equations, PDEs, Tesla K20

February 17, 2014 by hgpu

Hybrid strategy for stencil computations on the APU

Pacome Eberhart, Issam Said, Pierre Fortin

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Tags: AMD, APU, Computer science, Numerical Analysis, OpenCL, Partial differential equations

January 26, 2014 by hgpu

Multilayered Abstractions for Partial Differential Equations

Graham Robert Markall

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Code generation, CUDA, Differential equations, FEM, Finite element method, Mathematics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Partial differential equations, PDEs, Software Engineering, Thesis

December 11, 2013 by hgpu

GPU-Accelerated Crack Path Computation Based on a Phase Field Approach for Brittle Fracture

Alexander Schluter, Adrian Willenbucher, Charlotte Kuhn

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Tags: Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla C2075

December 8, 2013 by hgpu

GPU-Based Image Segmentation Using Level Set Method With Scaling Approach

Zafer Guler, Ahmet Cinar

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Tags: Algorithms, CUDA, Image processing, MRI, nVidia, nVidia GeForce GTX 660 Ti, Partial differential equations, PDEs

October 30, 2013 by hgpu

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

Daniel N. Benedetti, W. Randolph Franklin, Wenli Li

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Tags: Algorithms, Compression, CUDA, Differential equations, Image processing, nVidia, Partial differential equations, PDEs, Thrust

October 10, 2013 by hgpu

Multi-GPU Acceleration of Black-Scholes Equation based Option Pricing

Di Zhao, Jinhang Yu

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Tags: Algorithms, CUDA, Differential equations, Finance, nVidia, nVidia GeForce GTX 660, Partial differential equations, PDEs

September 23, 2013 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Initial condition for efficient mapping of level set algorithms on many-core architectures

Development of High-Performance Software Components for Emerging Architectures

GPU Accelerated Discontinuous Galerkin Methods for Shallow Water Equations

A GPU Accelerated Aggregation Algebraic Multigrid Method

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

Optimizing Performance of Stencil Code with SPL Conqueror

Hybrid strategy for stencil computations on the APU

Multilayered Abstractions for Partial Differential Equations

GPU-Accelerated Crack Path Computation Based on a Phase Field Approach for Brittle Fracture

GPU-Based Image Segmentation Using Level Set Method With Scaling Approach

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

Multi-GPU Acceleration of Black-Scholes Equation based Option Pricing

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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