high performance computing on graphics processing units: hgpu.org

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MatConvNet – Convolutional Neural Networks for MATLAB

Andrea Vedaldi, Karel Lenc

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Neural and Evolutionary Computing, Neural networks, nVidia

December 16, 2014 by hgpu

Conjugate gradient solvers on Intel Xeon Phi and NVIDIA GPUs

O. Kaczmarek, C. Schmidt, P. Steinbrecher, M. Wagner

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Tags: Computational Physics, Conjugate gradient solver, CUDA, High Energy Physics - Lattice, Intel Xeon Phi, Mathematical Software, nVidia, Physics, Tesla K20, Tesla K40

November 18, 2014 by hgpu

cuDNN: Efficient Primitives for Deep Learning

Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, Evan Shelhamer

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Tags: Computer science, CUDA, Machine learning, Mathematical Software, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Tesla K40

October 8, 2014 by hgpu

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

Ahmad Abdelfattah, David Keyes, Hatem Ltaief

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Mathematical Software, nVidia, Package, Tesla K20

October 8, 2014 by hgpu

Enhancing R with Advanced Compilation Tools and Methods

Duncan Temple Lang

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Tags: Computer science, CUDA, Mathematical Software, nVidia, Programming Languages

September 11, 2014 by hgpu

A Framework for Lattice QCD Calculations on GPUs

F. T. Winter, M. A. Clark, R. G. Edwards, B. Joo

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Tags: Algorithms, Code generation, Computational Physics, CUDA, High Energy Physics - Lattice, Mathematical Software, nVidia, Physics, PTX, QCD, Tesla K20

August 27, 2014 by hgpu

COFFEE: an Optimizing Compiler for Finite Element Local Assembly

Fabio Luporini, Ana Lucia Varbanescu, Florian Rathgeber, Gheorghe-Teodor Bercea, J. Ramanujam, David A. Ham, Paul H.J. Kelly

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Tags: Compilers, Computer science, Differential equations, FEM, Finite element method, Intel Xeon Phi, Mathematical Software, Partial differential equations, PDEs

July 10, 2014 by hgpu

A Scala Prototype to Generate Multigrid Solver Implementations for Different Problems and Target Multi-Core Platforms

Harald Koestler, Christian Schmitt, Sebastian Kuckuk, Frank Hannig, Juergen Teich, Ulrich Ruede

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Tags: Algorithms, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, nVidia GeForce GTX 680, Partial differential equations, PDEs

June 23, 2014 by hgpu

Increasing precision of uniform pseudorandom number generators

Vadim Demchik, Alexey Gulov

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Tags: Algorithms, Computer science, Extended precision, Mathematical Software, Pseudo-random number generators, Security

February 12, 2014 by hgpu

A study of the speed and the accuracy of the Boundary Element Method as applied to the computational simulation of biological organs

Kirana Kumara P

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Tags: Computational Physics, Computer science, CUDA, Fortran, Mathematical Software, Medical Physics, MPI, nVidia, nVidia Quadro 4000, Package

November 19, 2013 by hgpu

Lattice Simulations using OpenACC compilers

Pushan Majumdar

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, Mathematical Software, nVidia, OpenACC, Physics, Tesla X2090

November 13, 2013 by hgpu

GooFit: A library for massively parallelising maximum-likelihood fits

R. Andreassen, B. T. Meadows, M. de Silva, M. D. Sokoloff, K. Tomko

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Tags: Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GT 650 M, Package, Probability, Tesla C2050, Tesla C2070

November 8, 2013 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

MatConvNet – Convolutional Neural Networks for MATLAB

Conjugate gradient solvers on Intel Xeon Phi and NVIDIA GPUs

cuDNN: Efficient Primitives for Deep Learning

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

Enhancing R with Advanced Compilation Tools and Methods

A Framework for Lattice QCD Calculations on GPUs

COFFEE: an Optimizing Compiler for Finite Element Local Assembly

A Scala Prototype to Generate Multigrid Solver Implementations for Different Problems and Target Multi-Core Platforms

Increasing precision of uniform pseudorandom number generators

A study of the speed and the accuracy of the Boundary Element Method as applied to the computational simulation of biological organs

Lattice Simulations using OpenACC compilers

GooFit: A library for massively parallelising maximum-likelihood fits

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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