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Implementing Push-Pull Efficiently in GraphBLAS

Carl Yang, Aydin Buluc, John D. Owens

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Tags: Algorithm optimization, Algorithms, BLAS, Computer science, CUDA, Graph theory, Linear Algebra, nVidia, Sparse matrix, Tesla K40

April 15, 2018 by hgpu

Design Principles for Sparse Matrix Multiplication on the GPU

Carl Yang, Aydin Buluc, John D. Owens

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla K40

March 31, 2018 by hgpu

Technical Report about Tiramisu: a Three-Layered Abstraction for Hiding Hardware Complexity from DSL Compilers

Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane, Emanuele Del Sozzo, Patricia Suriana, Shoaib Kamil, Saman Amarasinghe

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Tags: Compilers, Computer science, DSL, FPGA, Matrix multiplication, nVidia, OpenMPI, Performance, Programming Languages, PTX, Tesla K40

March 3, 2018 by hgpu

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on Next-Generation Architectures

Simon Garcia De Gonzalo, Simon D. Hammond, Christian R. Trott, Wen-Mei Hwu

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Tags: Auto-Tuning, Computer science, CUDA, Intel Xeon Phi, nVidia, Sparse matrix, Tesla K20, Tesla K40, Tesla K80, Tesla P100

January 28, 2018 by hgpu

SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

Linnan Wang, Jinmian Ye, Yiyang Zhao, Wei Wu, Ang Li, Shuaiwen Leon Song, Zenglin Xu, Tim Kraska

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Tesla K40

January 20, 2018 by hgpu

ImageCL: Language and source-to-source compiler for performance portability, load balancing, and scalability prediction on heterogeneous systems

Thomas L. Falch, Anne C. Elster

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Tags: ATI, ATI Radeon HD 7970, Compilers, Heterogeneous systems, Image processing, Machine learning, nVidia, nVidia GeForce GTX 960, OpenCL, Package, performance portability, Tesla K40

January 13, 2018 by hgpu

Design and Implementation of the Futhark Programming Language

Troels Henriksen

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Tags: AMD FirePro W8100, ATI, Computer science, Haskell, High-level Languages, nVidia, OpenCL, Package, Tesla K40, Thesis

December 28, 2017 by hgpu

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

Lukas Polok

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Tags: Algorithms, Computer science, Differential equations, Factorization, FEM, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 680, OpenCL, Partial differential equations, PDEs, Sparse matrix, Tesla K40, Thesis

December 19, 2017 by hgpu

Implementing implicit OpenMP data sharing on GPUs

Gheorghe-Teodor Bercea, Carlo Bertolli, Arpith C. Jacob, Alexandre Eichenberger, Alexey Bataev, Georgios Rokos, Hyojin Sung, Tong Chen, Kevin O'Brien

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Tags: Computer science, CUDA, LLVM, Memory model, nVidia, OpenMP, Programming Languages, PTX, Tesla K40, Tesla P100

November 30, 2017 by hgpu

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Marcio M. Pereira, Rafael C. F. Sousa, Guido Araujo

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Tags: ARM, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, LLVM, nVidia, OpenCL, OpenMP, Package, Tesla K40

November 21, 2017 by hgpu

Hydra: a C++11 framework for data analysis in massively parallel platforms

A. A. Alves Junior, M. D. Sokoloff

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Tags: Computational Physics, Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, Tesla K40

November 16, 2017 by hgpu

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

Przemyslaw Stpiczynski

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Tags: Algorithms, Computer science, Intel Xeon Phi, Monte Carlo integration, nVidia, OpenACC, OpenMP, Pseudo-random number generators, Tesla K40

November 12, 2017 by hgpu

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DLL: Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

DLL: A Blazing Fast Deep Neural Network Library

HCC: Open Source, Optimizing C++ Compiler for Heterogeneous Compute for the ROCm GPU Computing Platform

Evaluating Performance Tradeoffs on the Radeon Open Compute Platform

pynufft: Python non-uniform fast Fourier transform (NUFFT)

Python Non-Uniform Fast Fourier Transform (PyNUFFT): An Accelerated Non-Cartesian MRI Package on a Heterogeneous Platform (CPU/GPU)

MALBEC: a new CUDA-C ray-tracer in General Relativity

Volna-OP2: OP2 port of the original Volna code

The VOLNA-OP2 Tsunami Code (Version 1.0)

CuLDA_CGS: Solving Large-scale LDA Problems on GPUs

MeterPU: Generic Portable Measurement Framework for Multicore CPU and Multi-GPU Systems

Programming Abstractions and Optimization Techniques for GPU-based Heterogeneous Systems

GHOST: General, Hybrid and Optimized Sparse Toolkit

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

Equalizer 2.0: Convergence of a Parallel Rendering Framework

Equalizer 2.0 – Convergence of a Parallel Rendering Framework

QMCPACK: An open source ab initio Quantum Monte Carlo package for the electronic structure of atoms, molecules, and solids

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high performance computing on graphics processing units: hgpu.org

Implementing Push-Pull Efficiently in GraphBLAS

Design Principles for Sparse Matrix Multiplication on the GPU

Technical Report about Tiramisu: a Three-Layered Abstraction for Hiding Hardware Complexity from DSL Compilers

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on Next-Generation Architectures

SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks

ImageCL: Language and source-to-source compiler for performance portability, load balancing, and scalability prediction on heterogeneous systems

Design and Implementation of the Futhark Programming Language

Accelerated Sparse Matrix Operations in Nonlinear Least Squares Solvers

Implementing implicit OpenMP data sharing on GPUs

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Hydra: a C++11 framework for data analysis in massively parallel platforms

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

Recent source codes

DLL: Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

HCC: Open Source, Optimizing C++ Compiler for Heterogeneous Compute for the ROCm GPU Computing Platform

pynufft: Python non-uniform fast Fourier transform (NUFFT)

MALBEC: a new CUDA-C ray-tracer in General Relativity

Volna-OP2: OP2 port of the original Volna code

CuLDA_CGS: Solving Large-scale LDA Problems on GPUs

MeterPU: Generic Portable Measurement Framework for Multicore CPU and Multi-GPU Systems

GHOST: General, Hybrid and Optimized Sparse Toolkit

Equalizer 2.0: Convergence of a Parallel Rendering Framework

QMCPACK: An open source ab initio Quantum Monte Carlo package for the electronic structure of atoms, molecules, and solids

Most viewed papers (last 30 days)

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International Conference on Biomedicine & Pharmacotherapy, 2018

8th International Workshop on Computer Science and Engineering (WCSE’18), 2018

International Conference on Robotics, Artificial Intelligence, Automation and Mechatronics, 2018

The 3rd IEEE International Conference on Image, Vision and Computing (ICIVC), 2018

The 2th International Conference on Robotics and Automation Sciences (ICRAS), 2018