high performance computing on graphics processing units: hgpu.org

Theses

hgpu.org » Applications

Acceleration of Deep Learning on FPGA

Huyuan Li

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Tags: CNN, Computer science, Deep learning, FPGA, Neural networks, nVidia, OpenCL, Tesla K40, Thesis

May 9, 2017 by hgpu

Automatic source code adaptation for heterogeneous platforms

Albert Saa-Garriga

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenMP, Tesla M2050, Thesis

April 30, 2017 by hgpu

Lattice Quantum Chromodynamics on Intel Xeon Phi based supercomputers

Peter Labus

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Tags: Algorithms, HEP, Heterogeneous systems, Intel Xeon Phi, OpenMP, Physics, QCD, Thesis

April 26, 2017 by hgpu

Developing a massive real-time crowd simulation framework on the GPU

Guillaume Payet

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Tags: Algorithms, Computer science, Crowd simulation, nVidia, nVidia GeForce GTX 850 M, OpenCL, Thesis

April 26, 2017 by hgpu

A Training Framework and Architectural Design for Distributed Deep Learning

Wei Wang

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Source codes

Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan X, Package, Python, Thesis

April 26, 2017 by hgpu

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

Pascal Libuschewski

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Tags: Biology, Computer vision, Design space exploration, Microscopy, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 560 Ti, nVidia Quadro NVS 3100 M, OpenCL, Thesis, Visualization

April 20, 2017 by hgpu

Evaluation of GPU-based track-triggering for the CMS detector at CERN’s HL-LHC

Hannes Mohr

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Tags: Algorithms, ASIC, CUDA, FPGA, HEP, nVidia, Physics, Tesla K40, Tesla K80, Thesis

April 20, 2017 by hgpu

Investigation of heterogeneous computing through novel parallel programming platforms

Andrei-Alexandru Dafinoiu

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Tags: ARM, ATI, ATI Radeon HD 6450, ATI Radeon HD 6570, Computer science, FPGA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 750 Ti, OpenCL, SoC, Thesis

April 17, 2017 by hgpu

Machine Learning from Streaming Data in Heterogeneous Computing Environments

Yusuf Guven Toprakkiran

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Thesis

April 11, 2017 by hgpu

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Maria Barreda Vaya

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Intel Xeon Phi, Linear Algebra, MPI, nVidia, OmpSs, Tesla C2050, Thesis

April 11, 2017 by hgpu

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Julian Romera

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenMPI, Performance, Tesla K80, Tesla M2090, Thesis

April 7, 2017 by hgpu

Pipelined MapReduce: A Decoupled MapReduce RunTime for Shared Memory Multi-Processors

Konstantinos Iliakis

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Tags: Computer science, Intel Xeon Phi, MapReduce, Thesis

March 28, 2017 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

Theses

Acceleration of Deep Learning on FPGA

Automatic source code adaptation for heterogeneous platforms

Lattice Quantum Chromodynamics on Intel Xeon Phi based supercomputers

Developing a massive real-time crowd simulation framework on the GPU

A Training Framework and Architectural Design for Distributed Deep Learning

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

Evaluation of GPU-based track-triggering for the CMS detector at CERN’s HL-LHC

Investigation of heterogeneous computing through novel parallel programming platforms

Machine Learning from Streaming Data in Heterogeneous Computing Environments

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Pipelined MapReduce: A Decoupled MapReduce RunTime for Shared Memory Multi-Processors

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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