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GPU Enhancement of the Trigger to Extend Physics Reach at the Large Hadron Collider

P. Lujan, V. Halyo, A. Hunt, P. Jindal, P. LeGresley

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Tags: Algorithms, CUDA, Instrumentation and Detectors, nVidia, Physics, Tesla C2075, Tesla K20

November 13, 2013 by hgpu

A Hybrid GPU/CPU FFT Library for Large FFT Problems

Shuo Chen

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Tags: Computer science, CUDA, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Tesla C2070, Tesla C2075, Thesis

November 12, 2013 by hgpu

PAKCK: Performance and Power Analysis of Key Computational Kernels on CPUs and GPUs

Julia S. Mullen, Michael M. Wolf, Anna Klein

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, Tesla C2075

November 3, 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 New Approach of Performance Analysis of Certain Graph Algorithms

M. F Mridha, Mohammad Manzurul Islam, Syed Mohammad Oliur Rahman

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Tags: Computer science, CUDA, Graph theory, nVidia, Tesla C2075

October 26, 2013 by hgpu

Towards a Unified Sentiment Lexicon (USL) based on Graphics Processing Units (GPUs)

Liliana Ibeth Barbosa-Santillan, Inmaculada Alvarez-de-Mon-y-Rego

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20

October 24, 2013 by hgpu

gEMpicker: A Highly Parallel GPU-Accelerated Particle Picking Tool for Cryo-Electron Microscopy

Thai V. Hoang, Xavier Cavin, Patrick Schultz, David W. Ritchie

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Tags: Algorithms, Biology, Cryo-EM, CUDA, Electron microscopy, FFT, Macromolecule, Microscopy, nVidia, Tesla C1060, Tesla C2075

October 24, 2013 by hgpu

Multiphase Flow Simulations in Inclined Tubes with Lattice Boltzmann Method on GPU

D.P. Khramtsov, D.A. Nekrasov, B.G. Pokusaev

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, Numerical simulation, nVidia, Tesla C2075

October 22, 2013 by hgpu

Construction of a Virtual Cluster by Integrating PCI Pass-Through for GPU and InfiniBand Virtualization in Cloud

Chao-Tung Yang, Wei-Shen Ou

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Tags: Cloud, Cluster computing, Computer science, CUDA, GPU cluster, nVidia, Tesla C2050, Tesla C2070, Tesla C2075, Tesla K20, Virtualization

October 19, 2013 by hgpu

Understanding and Modeling the Synchronization Cost in the GPU Architecture

James T. Letendre

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla C2075, Thesis

October 17, 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

Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

Blesson Varghese, Andrew Rau-Chaplin

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Tags: Computational Engineering, Computer science, CUDA, Finance, nVidia, Risk Management, Tesla C2075

October 10, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU Enhancement of the Trigger to Extend Physics Reach at the Large Hadron Collider

A Hybrid GPU/CPU FFT Library for Large FFT Problems

PAKCK: Performance and Power Analysis of Key Computational Kernels on CPUs and GPUs

Molecular Simulations using CUDA

A New Approach of Performance Analysis of Certain Graph Algorithms

Towards a Unified Sentiment Lexicon (USL) based on Graphics Processing Units (GPUs)

gEMpicker: A Highly Parallel GPU-Accelerated Particle Picking Tool for Cryo-Electron Microscopy

Multiphase Flow Simulations in Inclined Tubes with Lattice Boltzmann Method on GPU

Understanding and Modeling the Synchronization Cost in the GPU Architecture

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

Accounting for Secondary Uncertainty: Efficient Computation of Portfolio Risk Measures on Multi and Many Core Architectures

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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