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Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Konstantin Herb, Pol Welter

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Tags: BLAS, Computational Physics, Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla V100

August 22, 2021 by hgpu

Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs

Shandong Lao, Aaron Holt, Deepthi Vaidhynathan, Hariswaran Sitaraman, Christine M. Hrenya, Thomas Hauser

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Tags: cfd, CUDA, Fluid dynamics, HPC, nVidia, nVidia A100, Tesla V100

August 22, 2021 by hgpu

Better GPU Hash Tables

Muhammad A. Awad, Saman Ashkiani, Serban D. Porumbescu, Martín Farach-Colton, John D. Owens

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX Titan X

August 22, 2021 by hgpu

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Fabian Knorr, Peter Thoman, Thomas Fahringer

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, Package, SYCL, Tesla V100

August 8, 2021 by hgpu

Performance assessment of CUDA and OpenACC in large scale combustion simulations

Guillermo Oyarzun, Daniel Mira, Guillaume Houzeaux

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Tags: CUDA, nVidia, OpenACC, Performance, Physics, Tesla V100

August 8, 2021 by hgpu

Effective GPU Sharing Under Compiler Guidance

Chao Chen, Chris Porter, Santosh Pande

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Tags: Compilers, Computer science, CUDA, LLVM, Neural networks, nVidia, Tesla P100, Tesla V100

July 25, 2021 by hgpu

Optimisation and GPU code generation of Stencils for Futhark

Christian Charlie Virt, Jonathan Wraa-Hansen

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, nVidia GeForce RTX 2080 Ti, OpenCL, Performance, Thesis

July 18, 2021 by hgpu

GPTPU: Accelerating Applications using Edge Tensor Processing Units

Kuan-Chieh Hsu, Hung-Wei Tseng

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Machine learning, Neural networks, nVidia, OpenCL, TPU

July 18, 2021 by hgpu

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian Foster, Zhao Zhang

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia A100, nVidia DGX-A100, Package, Tesla V100

July 11, 2021 by hgpu

Dynamic Adaptation Techniques and Opportunities to Improve HPC Runtimes

Mohammad Alaul Haque Monil

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

July 11, 2021 by hgpu

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Dominik Ernst, Georg Hager, Markus Holzer, Matthias Knorr, Gerhard Wellein

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Tags: Code generation, Computer science, CUDA, Lattice Boltzmann model, Machine learning, nVidia, Performance, Stencil computation, Tesla V100

July 11, 2021 by hgpu

Optimization of Heterogeneous Parallel Computing Systems using Machine Learning

Devi Abhiseshu Adurti, Mohit Battu

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Matrix multiplication, nVidia, nVidia GeForce GTX 1050 Ti, Thesis

July 4, 2021 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

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high performance computing on graphics processing units: hgpu.org

Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines

Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs

Better GPU Hash Tables

ndzip-gpu: Efficient Lossless Compression of Scientific Floating-Point Data on GPUs

Performance assessment of CUDA and OpenACC in large scale combustion simulations

Effective GPU Sharing Under Compiler Guidance

Optimisation and GPU code generation of Stencils for Futhark

GPTPU: Accelerating Applications using Edge Tensor Processing Units

KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks

Dynamic Adaptation Techniques and Opportunities to Improve HPC Runtimes

Opening the Black Box: Performance Estimation during Code Generation for GPUs

Optimization of Heterogeneous Parallel Computing Systems using Machine Learning

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