high performance computing on graphics processing units: hgpu.org

hgpu.org » Mixed precision

Automatic code generation methods applied to numerical linear algebra in high performance computing

M. Ian Masliah

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Tags: Algorithms, Code generation, Computer science, CUDA, Heterogeneous systems, Linear Algebra, Mixed precision, nVidia, nVidia Tegra TX1, Programming techniques, Tesla C2075, Tesla K40, Thesis

November 16, 2016 by hgpu

Efficient and portable acceleration of quantum chemical many-body methods in mixed floating point precision using OpenACC compiler directives

Janus Juul Eriksen

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Tags: Chemical Physics, Chemistry, Mixed precision, nVidia, OpenACC, Physics, Tesla K40

September 27, 2016 by hgpu

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix decomposition, Mixed precision, Numerical Analysis, nVidia, Performance, Tesla K20

July 16, 2016 by hgpu

A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Lukas Einkemmer

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Tags: Computational Physics, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, Mixed precision, nVidia, OpenMP, Tesla K80

March 25, 2016 by hgpu

Optimising Reconfigurable Systems for Real-time Applications

Thomas Chun Pong Chau

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Tags: Algorithms, Computer science, CUDA, FPGA, Machine learning, Mixed precision, nVidia, Package, Tesla C2070, Thesis

August 7, 2015 by hgpu

Towards an automatic generation of dense linear algebra solvers on parallel architectures

Marc Baboulin, Joel Falcou, Ian Masliah

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Tags: Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, Tesla C2075

December 20, 2014 by hgpu

Mixed-precision orthogonalization scheme and its case studies with CA-GMRES on a GPU

Ichitaro Yamazaki, Stanimire Tomov, Tingxing Dong, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Mixed precision, nVidia, Tesla K20, Tesla K40, Tesla M2090

July 29, 2014 by hgpu

Adjoint Algorithmic Differentiation of a GPU Accelerated Application

Jacques du Toit, Johannes Lotz, Uwe Naumann

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Tags: Algorithms, Computer science, CUDA, Mixed precision, Monte Carlo simulation, nVidia, Tesla K20

November 2, 2013 by hgpu

Efficient CUDA polynomial preconditioned Conjugate Gradient solver for Finite Element computation of elasticity problems

Jianfei Zhang, Lei Zhang

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Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, Mixed precision, nVidia, nVidia GeForce GT 430, Sparse matrix

September 14, 2013 by hgpu

Local Volatility FX Basket Option on CPU and GPU

Jacques du Toit, Isabel Ehrlich

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Tags: CUDA, Finance, Mixed precision, nVidia, Tesla K20

May 19, 2013 by hgpu

Coulomb, Landau and Maximally Abelian Gauge Fixing in Lattice QCD with Multi-GPUs

Mario Schrock, Hannes Vogt

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Mixed precision, Monte Carlo simulation, MPI, nVidia, Physics, QCD, Tesla C2070

December 23, 2012 by hgpu

Optimization of power consumption in the iterative solution of sparse linear systems on graphics processors

Hartwig Anzt, Maribel Castillo, Juan C. Fernandez, Vincent Heuveline, Francisco D. Igual, Rafael Mayo and Enrique S. Quintana-Orti

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Mixed precision, nVidia, Tesla C1060

January 11, 2012 by hgpu

Page 1 of 312 3 »

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

gloo: Collective communications library with various primitives for multi-machine training

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated electromagnetic scattering by large ensembles of spheres

CELES: CUDA-accelerated simulation of electromagnetic scattering by large ensembles of spheres

Boda: A C++ Framework for Efficient Experiments in Computer Vision [WIP]

Implementing Efficient, Portable Computations for Machine Learning

ESPRESO: Highly Parallel Solvers for Engineering Applications

Intel Xeon Phi acceleration of Hybrid Total FETI solver

Parallel and in-process compilation of individuals for genetic programming on GPU

MECCA development in accelerators - KPP Fortran to CUDA source-to-source pre-processor

MEDINA: MECCA Development in Accelerators – KPP Fortran to CUDA source-to-source Preprocessor

Internally-maintained tool for examining GPU scheduling behavior

Inferring the Scheduling Policies of an Embedded CUDA GPU

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high performance computing on graphics processing units: hgpu.org

Automatic code generation methods applied to numerical linear algebra in high performance computing

Efficient and portable acceleration of quantum chemical many-body methods in mixed floating point precision using OpenACC compiler directives

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

A mixed precision semi-Lagrangian algorithm and its performance on accelerators

Optimising Reconfigurable Systems for Real-time Applications

Towards an automatic generation of dense linear algebra solvers on parallel architectures

Mixed-precision orthogonalization scheme and its case studies with CA-GMRES on a GPU

Adjoint Algorithmic Differentiation of a GPU Accelerated Application

Efficient CUDA polynomial preconditioned Conjugate Gradient solver for Finite Element computation of elasticity problems

Local Volatility FX Basket Option on CPU and GPU

Coulomb, Landau and Maximally Abelian Gauge Fixing in Lattice QCD with Multi-GPUs

Optimization of power consumption in the iterative solution of sparse linear systems on graphics processors

Recent source codes

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

gloo: Collective communications library with various primitives for multi-machine training

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated electromagnetic scattering by large ensembles of spheres

Boda: A C++ Framework for Efficient Experiments in Computer Vision [WIP]

ESPRESO: Highly Parallel Solvers for Engineering Applications

Parallel and in-process compilation of individuals for genetic programming on GPU

MECCA development in accelerators - KPP Fortran to CUDA source-to-source pre-processor

Internally-maintained tool for examining GPU scheduling behavior

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4th International Conference on Biomedical and Bioinformatics Engineering (ICBBE), 2017

9th International Conference on Signal Processing Systems (ICSPS), 2017

The 5th International conference on Control, Mechatronics and Automation (ICCMA), 2017

8th International Conference on Biology, Environment and Chemistry (ICBEC), 2017

2nd International Conference on Communication and Information Systems (ICCIS), 2017