high performance computing on graphics processing units: hgpu.org

hgpu.org » Differential equations

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

Ezhilmathi Krishnasamy, Pascal Bouvry

View

Download (PDF)

Source codes

Tags: BLAS, Computer science, CUDA, Differential equations, HPC, Linear Algebra, Matrix multiplication, nVidia, nVidia A100, OpenACC, Package, Partial differential equations, PDEs, Performance

December 24, 2024 by hgpu

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Sanil Rao, Mike Franusich, , Mohammad Alaul Haque Monil, Het Mankad, Jeffrey S. Vetter, Franz Franchetti

View

Download (PDF)

Tags: AMD, ATI, Code generation, Computer science, CUDA, Differential equations, Fortran, Heterogeneous systems, HIP, nVidia, OpenCL, OpenMP, Partial differential equations, PDEs

December 8, 2024 by hgpu

Automating Heterogeneous Parallelism in Numerical Differential Equations

Utkarsh

View

Download (PDF)

Source codes

Tags: AMD RX Vega 64, ATI, Computer science, CUDA, Differential equations, Factorization, Heterogeneous systems, Intel, Intel Arc A770, Julia, Numerical Analysis, nVidia, nVidia Quadro RTX 5000, Package, Tesla V100, Thesis

July 14, 2024 by hgpu

LeXInt: GPU-accelerated Exponential Integrators package

Pranab J. Deka, Alexander Moriggl, Lukas Einkemmer

View

Download (PDF)

Source codes

Tags: CUDA, Differential equations, Mathematics, nVidia, nVidia A100, Package

October 22, 2023 by hgpu

ProtoX: A First Look

Het Mankad, Sanil Rao, Brian Van Straalen, Phillip Colella, Franz Franchetti

View

Download (PDF)

Tags: Code generation, Computer science, Differential equations, Laplace and Poisson equation, Mathematical Software, Partial differential equations, PDEs, Poisson equation, Stencil computation

July 24, 2023 by hgpu

GPU Offloading in ExaHyPE Through C++ Standard Algorithms

Uzmar Gomez, Gonzalo Brito Gadeschi, Tobias Weinzierl

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, nVidia GeForce RTX 2080 Ti, OpenMP, Partial differential equations, PDEs

February 26, 2023 by hgpu

SciAI4Industry – Solving PDEs for industry-scale problems with deep learning

Philipp A. Witte, Russell J. Hewett, Kumar Saurabh, AmirHossein Sojoodi, Ranveer Chandra

View

Download (PDF)

Tags: AI, Cloud, Computational Physics, Computer science, Deep learning, Differential equations, Neural networks, nVidia, nVidia A100, nVidia DGX-A100, Partial differential equations, PDEs

November 27, 2022 by hgpu

Performance Assessment of using OpenCL on FPGA Systems for ODE Solvers

Patrick Tobias Haft

View

Download (PDF)

Tags: Code generation, Computational biology, Computer science, Differential equations, FPGA, nVidia, nVidia GeForce GTX 980 Ti, ODEs, OpenCL, Optimization, Ordinary differential equations, Tesla K20, Thesis

May 16, 2021 by hgpu

A Newcomer In The PGAS World – UPC++ vs UPC: A Comparative Study

Jérémie Lagravière, Johannes Langguth, Martina Prugger, Phuong H. Ha, Xing Cai

View

Download (PDF)

Source codes

Tags: Computer science, Differential equations, Distributed data structures, Intel Xeon Phi, Package

February 21, 2021 by hgpu

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Timo Betcke, Matthew W. Scroggs

View

Download (PDF)

Source codes

Tags: Computer science, Differential equations, Integral equations, OpenCL, Package, Partial differential equations, PDEs, Python

October 11, 2020 by hgpu

Unsupervised Deep Learning of Incompressible Fluid Dynamics

Nils Wandel, Michael Weinmann, Reinhard Klein

View

Download (PDF)

Tags: Deep learning, Differential equations, Fluid dynamics, Fluid simulation, Neural networks, nVidia, nVidia GeForce GTX 2080 Ti, Partial differential equations, PDEs, PyTorch

June 21, 2020 by hgpu

SODECL: An Open Source Library for Calculating Multiple Orbits of a System of Stochastic Differential Equations in Parallel

Eleftherios Avramidis, Marta Lalik, Ozgur E. Akman

View

Download (PDF)

Source codes

Tags: AMD FirePro W8100, ATI, Computer science, Differential equations, Mathematical Software, nVidia, OpenCL, Package, Tesla V100

August 18, 2019 by hgpu

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Automating Heterogeneous Parallelism in Numerical Differential Equations

LeXInt: GPU-accelerated Exponential Integrators package

ProtoX: A First Look

GPU Offloading in ExaHyPE Through C++ Standard Algorithms

Performance Assessment of using OpenCL on FPGA Systems for ODE Solvers

A Newcomer In The PGAS World – UPC++ vs UPC: A Comparative Study

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Unsupervised Deep Learning of Incompressible Fluid Dynamics

SODECL: An Open Source Library for Calculating Multiple Orbits of a System of Stochastic Differential Equations in Parallel

Recent source codes

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Most viewed papers (last 30 days)