high performance computing on graphics processing units: hgpu.org

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Synergia CUDA: GPU-accelerated accelerator modeling package

Q. Lu, J. Amundson

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Tags: CUDA, FFT, GPU cluster, MPI, nVidia, Package, Particle-in-cell methods, Physics, Tesla C1070, Tesla K20

June 17, 2014 by hgpu

GPU implementation of a hybrid lattice Boltzmann method for non-isothermal flows

Nachiket Sahasrabudhe, Mahesh Mynam, Ajay Nandgaonkar, Gayathri Jayaraman

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Tags: Algorithms, CUDA, Finite difference, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C1070

September 4, 2012 by hgpu

An Energy-Efficient Heterogeneous System for Embedded Learning and Classification

Abhinandan Majumdar, Srihari Cadambi, Srimat T. Chakradhar

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Tags: Computer science, Energy-efficient computing, FPGA, Heterogeneous systems, nVidia, nVidia ION, Tesla C1070

January 20, 2012 by hgpu

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

Wenjing Ma, Sriram Krishnamoorthy, Oreste Villa, Karol Kowalski

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Tags: Computational chemistry, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Presentation, Tesla C1070, Tesla S1070

July 7, 2011 by hgpu

Astrophysical Particle Simulations with Custom GPU Clusters

R. Spurzem, P. Berczik, K. Nitadori, G. Marcus, A. Kugel, R. Manner, I. Berentzen, R. Klessen, R. Banerjee

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Tags: Astrophysics, CUDA, GPU cluster, MPI, N-body simulation, nVidia, Tesla C1070, Tesla C870

May 19, 2011 by hgpu

Modeling the propagation of elastic waves using spectral elements on a cluster of 192 GPUs

Dimitri Komatitsch, Dominik Goddeke, Gordon Erlebacher, David Michea

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Tags: CUDA, Earth and Space Sciences, Geoscience, GPU cluster, MPI, nVidia, Tesla C1070

November 18, 2010 by hgpu

GPU-based ultrafast IMRT plan optimization

Chunhua Men,Xuejun Gu,Dongju Choi,Amitava Majumdar,Ziyi Zheng,Klaus Mueller,Steve B. Jiang

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Tags: CUDA, Medicine, nVidia, nVidia GeForce 9500 GT, nVidia GeForce GTX 285, Tesla C1060, Tesla C1070

October 27, 2010 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Synergia CUDA: GPU-accelerated accelerator modeling package

GPU implementation of a hybrid lattice Boltzmann method for non-isothermal flows

An Energy-Efficient Heterogeneous System for Embedded Learning and Classification

Acceleration of Streamed Tensor Contraction Expressions on GPGPU-Based Clusters

Astrophysical Particle Simulations with Custom GPU Clusters

Modeling the propagation of elastic waves using spectral elements on a cluster of 192 GPUs

GPU-based ultrafast IMRT plan optimization

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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