high performance computing on graphics processing units: hgpu.org

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Acceleration of tensor-product operations for high-order finite element methods

Kasia Swirydowicz, Noel Chalmers, Ali Karakus, Timothy Warburton

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Tags: Computer science, CUDA, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Overview, Performance, Tesla P100

November 7, 2017 by hgpu

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Michel Muller, Takayuki Aoki

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Tags: Earth and Space Sciences, Fortran, nVidia, OpenACC, OpenMP, Package, Tesla K20, Tesla P100, Weather prediction, Weather Prediction Model

October 29, 2017 by hgpu

GooFit 2.0

Henry Schreiner, Christoph Hasse, Bradley Hittle, Himadri Pandey, Michael Sokoloff, Karen Tomko

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Tags: Computer science, CUDA, Mathematical Software, MPI, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, Package, Probability, Tesla K40, Tesla P100

October 29, 2017 by hgpu

Deep Voice 3: 2000-Speaker Neural Text-to-Speech

Wei Ping, Kainan Peng, Andrew Gibiansky, Sercan O. Arik, Ajay Kannan, Sharan Narang, Jonathan Raiman, John Miller

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Tags: Computer science, CUDA, Deep learning, nVidia, Speech recognition, Tesla P100

October 24, 2017 by hgpu

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

Adam Stooke, Pieter Abbeel

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Tags: Computer science, CUDA, Data parallelism, Deep learning, nVidia, nVidia DGX-1, Package, Tesla P100, Theano

October 15, 2017 by hgpu

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

Marco Tazzari, Frederik Beaujean, Leonardo Testi

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 1060, Package, Python, Tesla P100

September 28, 2017 by hgpu

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

Dalal Sukkari, Hatem Ltaief, Mathieu Faverge, David Keyes

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Tags: Algorithms, Benchmarking, Computer science, Factorization, Intel Xeon Phi, nVidia, StarPU, Task scheduling, Tesla K80, Tesla P100

September 21, 2017 by hgpu

Report: Performance comparison between C2075 and P100 GPU cards using cosmological correlation functions

Miguel Cardenas-Montes, Ivan Mendez-Jimenez, Juan Jose Rodriguez-Vazquez, Jose Maria Hernandez Calama

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C2075, Tesla P100

September 12, 2017 by hgpu

Beyond 16GB: Out-of-Core Stencil Computations

Istvan Z. Reguly, Gihan R. Mudalige, Michael B. Giles

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Tags: Computer science, CUDA, Intel Xeon Phi, MPI, nVidia, Stencil computation, Tesla P100

September 9, 2017 by hgpu

FLASH: Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search

Yiqiu Wang, Anshumali Shrivastava, Junghee Ryu

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Tags: Algorithms, Computer science, Hashing, Machine learning, Nearest neighbour, nVidia, OpenCL, OpenMP, Tesla P100

September 7, 2017 by hgpu

From MPI to MPI+OpenACC: Conversion of a legacy FORTRAN PCG solver for the spherical Laplace equation

Ronald M. Caplan, Zoran Mikic, Jon A. Linker

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Tags: Computer science, CUDA, Fortran, Laplace and Poisson equation, Mathematical Software, MPI, nVidia, OpenACC, performance portability, Tesla P100

September 7, 2017 by hgpu

Towards On-Chip Optical FFTs for Convolutional Neural Networks

Jonathan George, Hani Nejadriahi, Volker Sorger

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Tags: CNN, Computer science, Deep learning, FFT, Neural networks, nVidia, Tesla P100

September 3, 2017 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

Acceleration of tensor-product operations for high-order finite element methods

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

GooFit 2.0

Deep Voice 3: 2000-Speaker Neural Text-to-Speech

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

GALARIO: a GPU Accelerated Library for Analysing Radio Interferometer Observations

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

Report: Performance comparison between C2075 and P100 GPU cards using cosmological correlation functions

Beyond 16GB: Out-of-Core Stencil Computations

FLASH: Randomized Algorithms Accelerated over CPU-GPU for Ultra-High Dimensional Similarity Search

From MPI to MPI+OpenACC: Conversion of a legacy FORTRAN PCG solver for the spherical Laplace equation

Towards On-Chip Optical FFTs for Convolutional Neural Networks

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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