high performance computing on graphics processing units: hgpu.org

hgpu.org » Electrodynamics

A Multi-GPU Sources Reconstruction Method for Imaging Applications

Miguel Lopez-Portugues, Yuri Alvarez, Jesus A. Lopez-Fernandez, Cebrian Garcia, Rafael G. Ayestaran, Fernando Las-Heras

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Tags: CUDA, Electrodynamics, GPU cluster, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 680, Signal processing

February 6, 2013 by hgpu

Hybrid Single/Double Precision Floating-Point Computation on GPU Accelerators for 2-D FDTD

Hasitha Muthumala Waidyasooriya, Yasuhiro Takei, Masanori Hariyama, Michitaka Kameyama

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Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, nVidia GeForce GTX 590

January 24, 2013 by hgpu

Analysis of Metallic Nanostructures by a Discontinuous Galerkin Time-Domain Maxwell Solver on Graphics Processing Units

Richard Timothy Helmut Diehl

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Tags: CUDA, Electrodynamics, Maxwell's equations, nVidia, nVidia GeForce GTX 580, Thesis

January 22, 2013 by hgpu

Implementation of FDTD-Compatible Green’s Function on Heterogeneous CPU-GPU Parallel Processing System

Tomasz P. Stefanski

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Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, Heterogeneous systems, nVidia, nVidia GeForce GTX 680

January 8, 2013 by hgpu

Theoretical and Numerical Analysis of Three Approaches to the GPGPU Application of the Explicit FDTD Method

Aude Giraud

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Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, Numerical Analysis, nVidia, Tesla T10, Thesis

December 18, 2012 by hgpu

Accuracy, Memory, and Speed Strategies in GPU-Based Finite-Element Matrix-Generation

Adam Dziekonski, Piotr Sypek, Adam Lamecki, Michal Mrozowski

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Tags: CUDA, Electrodynamics, FEM, Finite element method, nVidia, Optimization, Tesla C2075

December 16, 2012 by hgpu

Development of a CUDA Implementation of the 3D FDTD Method

Matthew Livesey, James Francis Stack, Jr., Fumie Costen, Takeshi Nanri, Norimasa Nakashima, Seiji Fujino

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Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, Tesla M2050, Tesla T10

December 12, 2012 by hgpu

CUDA-OpenGL Interoperability to Visualize Electromagnetic Fields Calculated by FDTD

Veysel Demir, Atef Z. Elsherbeni

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Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, OpenGL, Tesla C1060, Visualization

December 1, 2012 by hgpu

Fast Gpu-Based Interpolation for SAR Backprojection

A. Capozzoli, C. Curcio, A. Liseno

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Tags: Algorithms, CUDA, Electrodynamics, FFT, nVidia, Tesla C2050

November 11, 2012 by hgpu

Resolution of the Vlasov-Maxwell system by PIC Discontinuous Galerkin method on GPU with OpenCL

Anais Crestetto, Philippe Helluy

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Tags: ATI, ATI Radeon HD 5750, Electrodynamics, Maxwell's equations, nVidia, nVidia GeForce GTX 470, OpenCL, Particle-in-cell methods

September 24, 2012 by hgpu

A stand-alone Finite Difference Time Domain (FDTD) simulation for Integrated Optoelectronics Laboratory

Sathya Swaroop Ganta

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Tags: CUDA, Differential equations, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, Maxwell's equations, nVidia, nVidia GeForce 8400 GS, Optoelectronics, Python, Tesla C2075, Thesis

July 13, 2012 by hgpu

The Case for Higher Computational Density in the Memory-Bound FDTD Method within Multicore Environments

Mohammed F. Hadi

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Tags: Algorithms, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, Tesla C2050

April 27, 2012 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

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

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

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

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

See all packages

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high performance computing on graphics processing units: hgpu.org

A Multi-GPU Sources Reconstruction Method for Imaging Applications

Hybrid Single/Double Precision Floating-Point Computation on GPU Accelerators for 2-D FDTD

Analysis of Metallic Nanostructures by a Discontinuous Galerkin Time-Domain Maxwell Solver on Graphics Processing Units

Implementation of FDTD-Compatible Green’s Function on Heterogeneous CPU-GPU Parallel Processing System

Theoretical and Numerical Analysis of Three Approaches to the GPGPU Application of the Explicit FDTD Method

Accuracy, Memory, and Speed Strategies in GPU-Based Finite-Element Matrix-Generation

Development of a CUDA Implementation of the 3D FDTD Method

CUDA-OpenGL Interoperability to Visualize Electromagnetic Fields Calculated by FDTD

Fast Gpu-Based Interpolation for SAR Backprojection

Resolution of the Vlasov-Maxwell system by PIC Discontinuous Galerkin method on GPU with OpenCL

A stand-alone Finite Difference Time Domain (FDTD) simulation for Integrated Optoelectronics Laboratory

The Case for Higher Computational Density in the Memory-Bound FDTD Method within Multicore Environments

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

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