high performance computing on graphics processing units: hgpu.org

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A Comparison of Two Methods for Geometric Milling Simulation Accelerated by GPU

Masatomo Inui, Nobuyuki Umezu, Yuuki Shinozuka

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Rendering

October 29, 2013 by hgpu

Molecular Simulations using CUDA

Gerhard Burger

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Tags: CUDA, Molecular dynamics, Molecular simulation, Monte Carlo simulation, nVidia, nVidia GeForce GT 520, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla C2075, Thesis

October 29, 2013 by hgpu

A Datalog Engine for GPUs

Carlos Alberto Martinez-Angeles, Ines Dutra, Vitor Santos Costa, Jorge Buenabad-Chavez

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 580

October 25, 2013 by hgpu

Moim: A Multi-GPU MapReduce Framework

Mengjun Xie, Kyoung-Don Kang, Can Basaran

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Tags: Computer science, CUDA, MapReduce, MPI, nVidia, nVidia GeForce GTX 580, Thrust

October 21, 2013 by hgpu

Work Efficient Parallel Algorithms for Large Graph Exploration

Dip Sankar Banerjee, Shashank Sharma, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

October 21, 2013 by hgpu

Real-time computation of interactive waves using the GPU

Martijn de Jong, Auke van der Ploeg, Auke Ditzel, Kees Vuik

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 580

October 17, 2013 by hgpu

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

Stefan Kiel, Ekaterina Auer, Andreas Rauh

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 580, ODEs, Ordinary differential equations

October 15, 2013 by hgpu

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Jonathan Passerat-Palmbach

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Tags: Algorithms, Computer science, CUDA, Java, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Pseudo-random number generators, Software Engineering, Stochastic simulation, Tesla C2050, Tesla C2075, Tesla K20, Thesis

October 13, 2013 by hgpu

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

You-Liang Zhu, Hong Liu, Zhan-Wei Li, Hu-Jun Qian, Giuseppe Milano, Zhong-Yuan Lu

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Tags: Chemical Physics, Computational Physics, CUDA, Molecular simulation, nVidia, nVidia GeForce GTX 580, Phase transition, Physics, Soft Condensed Matter, Tesla K20

October 10, 2013 by hgpu

Enabling the use of Heterogeneous Computing for Bioinformatics

Ramakrishna Bijanapalli Chakri

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Tags: Bioinformatics, Biology, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Smith-Waterman algorithm, Thesis

October 8, 2013 by hgpu

Numerical integration on GPUs for higher order finite elements

Krzysztof Banas, Przemyslaw Plaszewski, Pawel Maciol

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Tags: ATI, ATI Radeon HD 5870, Computer science, FEM, Finite element method, Mathematical Software, nVidia, nVidia GeForce GTX 580, OpenCL

October 7, 2013 by hgpu

Parametric GPU Code Generation for Affine Loop Programs

Athanasios Konstantinidis, Paul H. J. Kelly, J. Ramanujam, P. Sadayappan

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Source codes

Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 580, OpenCL, Package, Tesla K20, Tesla M2070

October 5, 2013 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

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high performance computing on graphics processing units: hgpu.org

A Comparison of Two Methods for Geometric Milling Simulation Accelerated by GPU

Molecular Simulations using CUDA

A Datalog Engine for GPUs

Moim: A Multi-GPU MapReduce Framework

Work Efficient Parallel Algorithms for Large Graph Exploration

Real-time computation of interactive waves using the GPU

Uses of GPU Powered Interval Optimization for Parameter Identification in the Context of SO Fuel Cells

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

Enabling the use of Heterogeneous Computing for Bioinformatics

Numerical integration on GPUs for higher order finite elements

Parametric GPU Code Generation for Affine Loop Programs

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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