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Recent progress and challenges in exploiting graphics processors in computational fluid dynamics

Kyle E Niemeyer, Chih-Jen Sung

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Tags: Algorithms, Computational Physics, CUDA, Fluid dynamics, Lattice Boltzmann model, Navier-Stokes equations, NSEs, nVidia, OpenACC, Package, Review, Tesla C2075

September 13, 2013 by hgpu

The discrete dipole approximation code DDscat.C++: features, limitations and plans

V. Ya. Choliy

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Tags: Astrophysics, CUDA, Fortran, nVidia, nVidia GeForce GTX 260, Package

September 4, 2013 by hgpu

Detecting multiple periodicities in observational data with the multi-frequency periodogram. II. Frequency Decomposer, a parallelized time-series analysis algorithm

Roman V. Baluev

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Tags: Algorithms, Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GT 210, Package

September 4, 2013 by hgpu

Oncilla: A GAS Runtime for Efficient Resource Allocation and Data Movement in Accelerated Clusters

Jeff Young, Se Hoon Shon, Sudhakar Yalamanchili, Alex Merritt, Karsten Schwan

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Package

September 2, 2013 by hgpu

Computing High Resolution Explicit Corridor Maps using Parallel Technologies

R. Bonfiglioli

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Path problems, Thesis

August 31, 2013 by hgpu

Accelerating Text Mining Workloads in a MapReduce-based Distributed GPU Environment

Peter Wittek, Sandor Daranyi

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Tags: Algorithms, Computer science, CUDA, MapReduce, nVidia, Package, Self-organizing map, Tesla M2050, Text mining

August 31, 2013 by hgpu

The development and expansion of HOOMD-blue through six years of GPU proliferation

Joshua A. Anderson, Sharon C. Glotzer

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 580, nVidia GeForce GTX Titan, Package, Physics, Python, Software Engineering, Tesla S1070

August 27, 2013 by hgpu

Multiple Time Scales Recurrent Neural Network for Complex Action Acquisition

Martin Peniak, Davide Marocco, Jun Taniy, Yuichi Yamashitay, Kerstin Fischerz, Angelo Cangelosi

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Tags: Computer science, CUDA, Neural networks, nVidia, Package

August 27, 2013 by hgpu

Aquila 2.0: Software Architecture for Cognitive Robotics

Martin Peniak, Anthony Morse, Angelo Cangelosi

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Package

August 26, 2013 by hgpu

Estimating the WCET of GPU-Accelerated Applications using Hybrid Analysis

Adam Betts, Alastair Donaldson

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, OpenCL, Package, Python, Tesla C2050

August 26, 2013 by hgpu

OpenCL programming using Python syntax

Massimo Di Pierro

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Tags: Computer science, OpenCL, Package, PyOpenCL, Python

August 26, 2013 by hgpu

Estimation of Skin Optical Parameters for Real-Time Hyperspectral Imaging Applications using GPGPU Parallel Computing

Asgeir Bjorgan

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Tags: Algorithms, CUDA, Image processing, Monte Carlo simulation, nVidia, nVidia Quadro FX 3700 M, OpenCV, Optics, Package, Physics, Thesis, Visualization

August 23, 2013 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

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high performance computing on graphics processing units: hgpu.org

Applications

Recent progress and challenges in exploiting graphics processors in computational fluid dynamics

The discrete dipole approximation code DDscat.C++: features, limitations and plans

Detecting multiple periodicities in observational data with the multi-frequency periodogram. II. Frequency Decomposer, a parallelized time-series analysis algorithm

Oncilla: A GAS Runtime for Efficient Resource Allocation and Data Movement in Accelerated Clusters

Computing High Resolution Explicit Corridor Maps using Parallel Technologies

Accelerating Text Mining Workloads in a MapReduce-based Distributed GPU Environment

The development and expansion of HOOMD-blue through six years of GPU proliferation

Multiple Time Scales Recurrent Neural Network for Complex Action Acquisition

Aquila 2.0: Software Architecture for Cognitive Robotics

Estimating the WCET of GPU-Accelerated Applications using Hybrid Analysis

OpenCL programming using Python syntax

Estimation of Skin Optical Parameters for Real-Time Hyperspectral Imaging Applications using GPGPU Parallel Computing

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

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