high performance computing on graphics processing units: hgpu.org

hgpu.org » Mixed precision

NVIDIA Tensor Core Programmability, Performance & Precision

Stefano Markidis, Steven Wei Der Chien, Erwin Laure, Ivy Bo Peng, Jeffrey S. Vetter

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Tags: Computer science, CUDA, Mixed precision, nVidia, Performance, Tesla V100

March 17, 2018 by hgpu

Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

Azzam Haidar, Panruo Wu, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Artificial intelligence, BLAS, Computer science, Linar Algebra, Mixed precision, Neural networks, nVidia, Tesla P100

December 10, 2017 by hgpu

Mixed Precision Solver Scalable to 16000 MPI Processes for Lattice Quantum Chromodynamics Simulations on the Oakforest-PACS System

Taisuke Boku, Ishikawa Ken-Ichi, Yoshinobu Kuramashi, Lawrence Meadows

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Tags: Computational Physics, High Energy Physics - Lattice, Intel Xeon Phi, Mixed precision, MPI, OpenMP, Package, Physics, QCD

September 28, 2017 by hgpu

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

Page 1 of 312 3 »

HXTSort: a single header library including lightning fast Parallel Radix Sort macros

One machine, one minute, three billion tetrahedra

qcgpu-rust: A High Performance, Hardware accelerated, Quantum computer simulator in Rust

Simulating Quantum Computers Using OpenCL

hStreams-benchmark: The benchmark of Intel hStreams

Auto-tuning Streamed Applications on Intel Xeon Phi

Parabix

Multidimensional Parallelization for Streaming Text Processing Applications Based on Parabix Framework

HLS4ML

Fast inference of deep neural networks in FPGAs for particle physics

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high performance computing on graphics processing units: hgpu.org

NVIDIA Tensor Core Programmability, Performance & Precision

Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

Mixed Precision Solver Scalable to 16000 MPI Processes for Lattice Quantum Chromodynamics Simulations on the Oakforest-PACS System

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

Recent source codes

HXTSort: a single header library including lightning fast Parallel Radix Sort macros

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GENESYS: GPU system calls from on ROCm

SR-NMT: Implementation in pytorch of SR-NMT

dlbench: Benchmarking State-of-the-Art Deep Learning Software Tools

qcgpu-rust: A High Performance, Hardware accelerated, Quantum computer simulator in Rust

hStreams-benchmark: The benchmark of Intel hStreams

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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