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Autotuning OpenACC Work Distribution via Direct Search

Calvin Montgomery, Jeffrey L. Overbey, Xuechao Li

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Tags: Computer science, MPI, nVidia, OpenACC, Package, Performance, Python, Tesla K20

July 8, 2015 by hgpu

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

Anton Akusok, Kaj-Mikael Bjork, Yoan Miche, Amaury Lendasse

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, OpenCL, Package, Python

July 6, 2015 by hgpu

RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

Nicholas P. Bailey, Trond S. Ingebrigtsen, Jesper Schmidt Hansen, Arno A. Veldhorst, Lasse Bohling, Claire A. Lemarchand, Andreas E. Olsen, Andreas K. Bacher, Heine Larsen, Jeppe C. Dyre, Thomas B. Schroder

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 780 Ti, Package, Physics, Python

June 17, 2015 by hgpu

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Christopher D. Cooper, Lorena A. Barba

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Tags: Biomolecules, Boltzmann equation, Computational Physics, CUDA, Electrostatics, nVidia, Package, Physics, Poisson Boltzmann, Python, Tesla C2075

June 14, 2015 by hgpu

Blocks and Fuel: Frameworks for deep learning

Bart van Merrienboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, Yoshua Bengio

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Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, MPI, Neural networks, nVidia, Package, Python, Symbolic Computation, Visualization

June 5, 2015 by hgpu

GPU-accelerated micromagnetic simulations using cloud computing

C. L. Jermain, G. E. Rowlands, R. A. Buhrman, D. C. Ralph

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Tags: Cloud, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 770, nVidia GRID K520, Package, Physics, Python

May 10, 2015 by hgpu

Fireflies: New software for interactively exploring dynamical systems using GPU computing

Robert Merrison-Hort

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Tags: Computer science, Differential equations, Mathematical Software, Mathematics, nVidia, nVidia GeForce GTX 460, ODEs, OpenCL, Ordinary differential equations, Package, Python

May 7, 2015 by hgpu

PyTransit: Fast and Easy Exoplanet Transit Modelling in Python

Hannu Parviainen

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Tags: Astrophysics, Earth and Planetary Astrophysics, OpenCL, Package, Python

May 3, 2015 by hgpu

Loo.py: From Fortran to performance via transformation and substitution rules

Andreas Klockner

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Tags: Code generation, Computer science, Fortran, OpenCL, Package, Python

March 28, 2015 by hgpu

Runtime Compilation of Array-Oriented Python Programs

Alex Rubinsteyn

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Python, Thesis

March 2, 2015 by hgpu

MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Ken Miura, Tetsuaki Mano, Atsushi Kanehira, Yuichiro Tsuchiya, Tatsuya Harada

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Tags: Computer science, Java, Machine learning, Mathematical Software, OpenCL, Package, Python

March 2, 2015 by hgpu

Comparison of SPMV performance on matrices with different matrix format using CUSP, cuSPARSE and ViennaCL

Ang Li, Hammad Mazhar, Radu Serban, Dan Negrut

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Tags: Computer science, CUDA, Linear Algebra, nVidia, OpenCL, Performance, Python, Sparse matrix, Tesla K20

February 22, 2015 by hgpu

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

OpScanner

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

Enhancing Transformer Performance and Portability through Auto-tuning Frameworks

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high performance computing on graphics processing units: hgpu.org

Autotuning OpenACC Work Distribution via Direct Search

High Performance Extreme Learning Machines: A Complete Toolbox for Big Data Applications

RUMD: A general purpose molecular dynamics package optimized to utilize GPU hardware down to a few thousand particles

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Blocks and Fuel: Frameworks for deep learning

Fireflies: New software for interactively exploring dynamical systems using GPU computing

PyTransit: Fast and Easy Exoplanet Transit Modelling in Python

Loo.py: From Fortran to performance via transformation and substitution rules

Runtime Compilation of Array-Oriented Python Programs

MILJS: Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

Comparison of SPMV performance on matrices with different matrix format using CUSP, cuSPARSE and ViennaCL

Recent source codes

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

pplx-garden: Perplexity open source garden for inference technology

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

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