high performance computing on graphics processing units: hgpu.org

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GPU accelerated molecular dynamics simulation of thermal conductivities

Juekuan Yang, Yujuan Wang, Yunfei Chen

Tags: Computational Physics, Molecular dynamics, nVidia, Physics

October 27, 2010 by hgpu

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

M. J. Harvey, G. Giupponi, G. De Fabritiis

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Tags: Biological Physics, Chemistry, Computational Physics, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce GTX 280, Package, Physics, Tesla C1060

October 27, 2010 by hgpu

Monte Carlo simulations on Graphics Processing Units

Vadim Demchik, Alexei Strelchenko

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Tags: ATI, ATI IL, ATI Radeon HD 4850, ATI Radeon HD 4870, ATI Stream, High Energy Physics - Lattice, Monte Carlo simulation, Physics

October 27, 2010 by hgpu

Simulating spin models on GPU

Martin Weigel

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Tags: CUDA, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Statistical Mechanics, Tesla C1060

October 27, 2010 by hgpu

Monte Carlo integration on GPU

J. Kanzaki

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Tags: Computational Physics, CUDA, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Monte Carlo integration, nVidia, nVidia GeForce GTX 285, Package, Physics

October 27, 2010 by hgpu

Computational advances in gravitational microlensing: a comparison of CPU, GPU, and parallel, large data codes

N. F. Bate, C. J. Fluke, B. R. Barsdell, H. Garsden, G. F. Lewis

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Tags: Astrophysics, CUDA, Gravitational lensing, Instrumentation and Methods for Astrophysics, nVidia, Tesla S1070

October 27, 2010 by hgpu

Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

Benjamin Block,Peter Virnau,Tobias Preis

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Tags: CUDA, GPU cluster, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Tesla C1060

October 27, 2010 by hgpu

A GPU based real-time software correlation system for the Murchison Widefield Array prototype

Randall B. Wayth,Lincoln J. Greenhill,Frank H. Briggs

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, Signal processing, Tesla C1060

October 27, 2010 by hgpu

Importance of Explicit Vectorization for CPU and GPU Software Performance

Neil G. Dickson, Kamran Karimi, Firas Hamze

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Tags: Computer science, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, Physics

October 27, 2010 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

Applications

GPU accelerated molecular dynamics simulation of thermal conductivities

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

Monte Carlo simulations on Graphics Processing Units

Simulating spin models on GPU

Monte Carlo integration on GPU

Computational advances in gravitational microlensing: a comparison of CPU, GPU, and parallel, large data codes

Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

A GPU based real-time software correlation system for the Murchison Widefield Array prototype

Importance of Explicit Vectorization for CPU and GPU Software Performance

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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