high performance computing on graphics processing units: hgpu.org

Theses

hgpu.org » Applications

Deep learning review and its applications

Andoni Azkarate Saiz

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 660, Review, Thesis

February 1, 2016 by hgpu

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Luka Stanisic

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla C2050, Tesla K20, Tesla K40, Tesla M2070, Tesla M2075, Thesis

February 1, 2016 by hgpu

GPU Based Methods for Interactive Information Visualization of Big Data

Peng Mi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenGL, Thesis, Visualization

January 29, 2016 by hgpu

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Tobias Klein

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Tags: Computer science, CUDA, DSL, Heterogeneous systems, Image processing, nVidia, nVidia Quadro 6000, OpenCL, Thesis, Visualization

January 29, 2016 by hgpu

Parallel Explicit FEM Algorithms Using GPU’s

Seyed Parsa Banihashemi

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Tags: Algorithms, AMD Radeon R9 280X, ATI, ATI Radeon HD 7970, Computer science, FEM, Finite element method, nVidia, nVidia GeForce GTX Titan, OpenCL, Particle swarm optimization, Performance, Tesla M2090, Thesis

January 22, 2016 by hgpu

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

Mohammed Abdelrahim

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Tags: Computer science, CUDA, Heterogeneous systems, LSTM, Machine learning, nVidia, nVidia GeForce GTX 770, OpenMP, Thesis

January 19, 2016 by hgpu

A framework for efficient execution on GPU and CPU+GPU systems

Jean-Francois Dollinger

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Performance, Thesis

January 19, 2016 by hgpu

Contributions of hybrid architectures to depth imaging: a CPU, APU and GPU comparative study

Issam Said

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Tags: APU, Computer science, Geophysics, Geoscience, GPU cluster, MPI, nVidia, OpenCL, Tesla K40, Thesis

January 16, 2016 by hgpu

GPU Remote Memory Access Programming

Jeremia Bar

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Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, OpenMPI, Tesla K80, Thesis

January 12, 2016 by hgpu

A Workload Balanced MapReduce Framework on GPU Platforms

Yue Zhang

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Tags: Benchmarking, Computer science, CUDA, MapReduce, nVidia, Performance, Tesla K40, Thesis

January 12, 2016 by hgpu

Batched Linear Algebra Problems on GPU Accelerators

Tingxing Dong

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40, Thesis

January 4, 2016 by hgpu

Programming Models and Scheduling Techniques for Heterogeneous Architectures

Judit Planas Carbonell

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OmpSs, Task scheduling, Tesla K20, Tesla K40, Tesla M2090, Thesis

January 4, 2016 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Theses

Deep learning review and its applications

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

GPU Based Methods for Interactive Information Visualization of Big Data

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Parallel Explicit FEM Algorithms Using GPU’s

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

A framework for efficient execution on GPU and CPU+GPU systems

Contributions of hybrid architectures to depth imaging: a CPU, APU and GPU comparative study

GPU Remote Memory Access Programming

A Workload Balanced MapReduce Framework on GPU Platforms

Batched Linear Algebra Problems on GPU Accelerators

Programming Models and Scheduling Techniques for Heterogeneous Architectures

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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