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A Domain Specific Language for Performance Portable Molecular Dynamics Algorithms

William R. Saunders, James Grant, Eike H. Muller

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Tags: Algorithms, Biology, Chemistry, Code generation, Computer science, CUDA, Differential equations, DSL, Molecular dynamics, nVidia, Package, Partial differential equations, PDEs, Physics, Python, Tesla K20

April 15, 2017 by hgpu

Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units

Ruxi Qi, Wesley M. Botello-Smith, Ray Luo

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Tags: Biomolecules, Biophysics, Boltzmann equation, Computational Physics, CUBLAS, CUDA, Electrostatics, Molecular simulation, nVidia, nVidia GeForce GTX 980 Ti, Physics, Poisson Boltzmann

April 11, 2017 by hgpu

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Maria Barreda Vaya

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Intel Xeon Phi, Linear Algebra, MPI, nVidia, OmpSs, Tesla C2050, Thesis

April 11, 2017 by hgpu

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

Siyang Qin, Roberto Manduchi

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Tags: Algorithms, Caffe, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan X

April 7, 2017 by hgpu

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Julian Romera

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenMPI, Performance, Tesla K80, Tesla M2090, Thesis

April 7, 2017 by hgpu

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Takuya Matsumoto, Kiminori Matsuzaki

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Tags: Computer science, CUDA, Haskell, Image processing, MRI, nVidia, nVidia GeForce GTX 750 Ti

April 3, 2017 by hgpu

Sparse Matrix-Vector Multiplication on GPGPUs

Salvatore Filippone, Valeria Cardellini, Davide Barbieri, Alessandro Fanfarillo

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Tags: Computer science, CUDA, Fortran, nVidia, nVidia GeForce GTX 660, Package, Review, Sparse matrix, Tesla K20, Tesla K40, Tesla M2070

April 3, 2017 by hgpu

Chai: Collaborative Heterogeneous Applications for Integrated-architectures

Juan Gomez-Luna, Izzat El Hajj, Li-Wen Chang, Victor Garcia-Flores, Simon Garcia de Gonzalo, Thomas B. Jablin, Antonio J. Pena, Wen-mei Hwu

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL

April 3, 2017 by hgpu

Energy conservation techniques for GPU computing

Xinxin Mei

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 780, nVidia GeForce GTX 980, Task scheduling, Thesis

March 28, 2017 by hgpu

Comparing Programmer Productivity in OpenACC and CUDA: an Empirical Investigation

Xuechao Li, Po-Chou Shih, Jeffrey Overbey, Cheryl Seals, Alvin Lim

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Tags: Computer science, CUDA, nVidia, OpenACC, Package

March 20, 2017 by hgpu

Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow

Francesco Giannini, Vincenzo Laveglia, Alessandro Rossi, Dario Zanca, Andrea Zugarini

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Tags: Computer science, CUDA, Deep learning, Machine learning, Matlab, Neural networks, nVidia, nVidia GeForce GTX 960, Package, TensorFlow, Torch

March 20, 2017 by hgpu

GPU accelerated population annealing algorithm

Lev Yu. Barash, Martin Weigel, Michal Borovsky, Wolfhard Janke, Lev N. Shchur

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Tags: Algorithms, CUDA, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Tesla K80

March 14, 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

A Domain Specific Language for Performance Portable Molecular Dynamics Algorithms

Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Sparse Matrix-Vector Multiplication on GPGPUs

Chai: Collaborative Heterogeneous Applications for Integrated-architectures

Energy conservation techniques for GPU computing

Comparing Programmer Productivity in OpenACC and CUDA: an Empirical Investigation

Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow

GPU accelerated population annealing algorithm

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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