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Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, S. Rajamanickam

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Tags: Computer science, CUDA, Differential equations, nVidia, OpenMP, Partial differential equations, PDEs, Tesla K20

November 24, 2015 by hgpu

Evaluating 3-D Stencil codes on Intel Xeon Phi: Limitations and Trade-offs

Mario Hernandez, Juan M. Cebrian, Jose M. Cecilia, Jose M. Garcia

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Tags: Algorithms, Computer science, Differential equations, Intel Xeon Phi, OpenMP, Partial differential equations, PDEs, Wave equation

November 11, 2015 by hgpu

Evaluation of the Intel Xeon Phi and NVIDIA K80 as accelerators for two-dimensional panel codes

Lukas Einkemmer

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Tags: Computer science, CUDA, Differential equations, Intel Xeon Phi, nVidia, Partial differential equations, PDEs, Performance, Tesla K80

November 10, 2015 by hgpu

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

Hector Dearman

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Tags: Benchmarking, Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, nVidia GRID K520, OpenCL, Partial differential equations, PDEs, Thesis

November 3, 2015 by hgpu

Toward a Multi-level Parallel Framework on GPU Cluster with PetSC-CUDA for PDE-based Optical Flow Computation

S. Cuomo, A. Galletti, G. Giunta, L. Marcellino

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Tags: Algorithms, Computer science, CUDA, Differential equations, GPU cluster, Heterogeneous systems, nVidia, nVidia Quadro K5000, Optical flow, Partial differential equations, PDEs

June 24, 2015 by hgpu

A Parallel Implementation of the Galerkin Method for Solving Partial Differential Equations on a Triangular Mesh

Rachel N. Hess

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Tags: Differential equations, FEM, Finite element method, Mathematics, OpenCL, Partial differential equations, PDEs, PyOpenCL, Thesis, Triangular meshes

June 7, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Source codes

Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 2015 by hgpu

A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms

Kooktae Lee, Raktim Bhattacharya, Vijay Gupta

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla C2050

March 18, 2015 by hgpu

Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA

Evan T. Dye

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Tags: Algorithms, Computer science, CUDA, Differential equations, Mathematics, nVidia, nVidia GeForce GTX 560 Ti, Partial differential equations, PDEs, Thesis

February 2, 2015 by hgpu

Productive and Efficient Computational Science Through Domain-specific Abstractions

Florian Rathgeber

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Tags: Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, OpenCL, Partial differential equations, PDEs, Thesis

February 1, 2015 by hgpu

A CUDA implementation of the High Performance Conjugate Gradient benchmark

Everett Phillips, Massimiliano Fatica

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla K20

November 29, 2014 by hgpu

A stencil-based implementation of Parareal in the C++ domain specific embedded language STELLA

Andrea Arteaga, Daniel Ruprecht, Rolf Krause

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Tags: Computer science, CUDA, Differential equations, MPI, nVidia, Partial differential equations, PDEs, Tesla K20

October 3, 2014 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

Evaluating 3-D Stencil codes on Intel Xeon Phi: Limitations and Trade-offs

Evaluation of the Intel Xeon Phi and NVIDIA K80 as accelerators for two-dimensional panel codes

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

Toward a Multi-level Parallel Framework on GPU Cluster with PetSC-CUDA for PDE-based Optical Flow Computation

A Parallel Implementation of the Galerkin Method for Solving Partial Differential Equations on a Triangular Mesh

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

A Switched Dynamical System Framework for Analysis of Massively Parallel Asynchronous Numerical Algorithms

Performance Analysis and Optimization of Hermite Methods on NVIDIA GPUs Using CUDA

Productive and Efficient Computational Science Through Domain-specific Abstractions

A CUDA implementation of the High Performance Conjugate Gradient benchmark

A stencil-based implementation of Parareal in the C++ domain specific embedded language STELLA

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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