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Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

Ricardo Javier Barrientos Rojel

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Search strategies, Tesla C1060, Tesla M2070, Thesis

December 6, 2013 by hgpu

A Fast Implementation of Parallel Discrete-Event Simulation on GPGPU

Janche Sang, Che-Rung Lee, Vernon Rego, Chung-Ta King

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla M2070, Thrust

December 6, 2013 by hgpu

NaNet:a low-latency NIC enabling GPU-based, real-time low level trigger systems

Roberto Ammendola, Andrea Biagioni, Riccardo Fantechi, Ottorino Frezza, Gianluca Lamanna, Francesca Lo Cicero, Alessandro Lonardo, Pier Stanislao Paolucci, Felice Pantaleo, Roberto Piandani, Luca Pontisso, Davide Rossetti, Francesco Simula, Marco Sozzi, Laura Tosoratto, Piero Vicini

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Tags: CUDA, FPGA, nVidia, Physics, Tesla K20, Tesla M2070

November 6, 2013 by hgpu

A Framework for Management of Distributed Data Processing and Event Selection for the Icecube Neutrino Observatory

Juan Carlos Diaz Velez

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Tags: CUDA, High Energy Physics - Experiment, nVidia, Physics, Python, Tesla C1060, Tesla C2050, Tesla M2070, Thesis

October 24, 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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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

Evaluation of disconnected quark loops for hadron structure using GPUs

C. Alexandrou, M. Constantinou, V. Drach, K. Hadjiyiannakou, K. Jansen, G. Koutsou, A. Strelchenko, A. Vaquero

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Tags: CUDA, High Energy Physics - Lattice, Nuclear Theory, nVidia, Physics, Tesla M2070

September 29, 2013 by hgpu

Re-Introduction of Communication-Avoiding FMM-Accelerated FFTs with GPU Acceleration

M. Harper Langston, Muthu Baskaran, Benoit Meister, Nicolas Vasilache, Richard Lethin

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Tags: Algorithms, CUDA, Fast multipole method, FFT, MPI, nVidia, Signal processing, Tesla M2070

September 29, 2013 by hgpu

Pipeline strategies to accelerate range query processing on a multi-GPU environment

Ricardo J. Barrientos

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Tags: Algorithms, Computer science, CUDA, Image recognition, nVidia, Tesla M2070

September 24, 2013 by hgpu

Preconditioned conjugate gradient solver for structural problems

Xiangge Li

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Tags: Computer science, Conjugate gradient solver, CUDA, nVidia, Physics, Tesla M2070

September 20, 2013 by hgpu

Using Modularity Metrics to assist Move Method Refactoring of Large System

Christian Napoli, Giuseppe Pappalardo, Emiliano Tramontana

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Software Engineering, Tesla M2070

August 20, 2013 by hgpu

Lattice Boltzmann Method for Simulating Turbulent Flows

Yusuke Koda

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Tags: Algorithms, CUDA, Fluid dynamics, Lattice Boltzmann model, Numerical simulation, nVidia, Tesla M2070, Thesis

August 14, 2013 by hgpu

GPU implementation of a shell element structural solver aimed at fluid-structure interaction problems

Andrea Bartezzaghi

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Tags: Algorithms, CUDA, FEM, Finite element method, Fluid dynamics, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 670 M, Tesla M2070, Thesis

August 8, 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 plugin for PySCF

Python-Based Quantum Chemistry Calculations with GPU Acceleration

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

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

Parallel Gaussian process with kernel approximation in CUDA

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