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Programming Abstractions and Optimization Techniques for GPU-based Heterogeneous Systems

Lu Li

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla C1060, Tesla C2050, Tesla K20, Tesla M2050, Thesis

March 10, 2018 by hgpu

Monte Carlo methods for massively parallel computers

Martin Weigel

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Tags: CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX Titan X, Phase transition, Physics, Spin Systems, Tesla C1060, Tesla K20

September 16, 2017 by hgpu

IODA: an Input/Output Deep Architecture for image labeling

J. Lerouge, R. Herault, Clement Chatelain, F. Jardin, R. Modzelewski

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Python, Tesla C1060, Theano

July 18, 2016 by hgpu

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Varun Nagpal

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C1060, Thesis

March 10, 2016 by hgpu

Togpu: Automatic Source Transformation from C++ to CUDA using Clang/LLVM

Matthew Marangoni, Thomas Wischgoll

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Tags: Code generation, Computer science, CUDA, Image processing, LLVM, nVidia, Tesla C1060

February 23, 2016 by hgpu

Efficient Query Processing in Co-Processor-accelerated Databases

Sebastian Bress

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Package, Tesla C1060, Tesla C2050, Thesis

December 19, 2015 by hgpu

On the programmability of multi-GPU computing systems

Javier Cabezas Rodriguez

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Tesla C1060, Tesla K20, Tesla K40, Thesis

November 3, 2015 by hgpu

Efficient Kernel Fusion Techniques for Massive Video Data Analysis on GPGPUs

Asif M Adnan, Sridhar Radhakrishnan, Suleyman Karabuk

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Tags: Algorithms, CUDA, Image processing, Neuroscience, nVidia, nVidia GeForce GTX 750 Ti, Tesla C1060, Tesla K20

September 17, 2015 by hgpu

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

Mehdi Amini

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Tags: ATI, ATI Radeon HD 6970, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 670, OpenCL, Tesla C1060, Tesla C2070, Thesis

August 24, 2015 by hgpu

CRINK: Automatic CUDA code generation for affine C programs

Akanksha Singh

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Tags: Code generation, Computer science, CUDA, nVidia, Tesla C1060, Thesis

August 10, 2015 by hgpu

Accelerating Protein Structure Prediction using Particle Swarm Optimization on GPU

Hamed Khakzad, Yasaman Karami, Seyed Shahriar Arab

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Particle swarm optimization, Sequence alignment, Tesla C1060

July 24, 2015 by hgpu

On the use of deep Boltzmann machines for road signs classification

Carlo D'Eramo

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Tags: Computer science, Computer vision, CUDA, Image recognition, Machine learning, nVidia, Python, Tesla C1060, Thesis

July 22, 2015 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

Programming Abstractions and Optimization Techniques for GPU-based Heterogeneous Systems

Monte Carlo methods for massively parallel computers

IODA: an Input/Output Deep Architecture for image labeling

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Togpu: Automatic Source Transformation from C++ to CUDA using Clang/LLVM

Efficient Query Processing in Co-Processor-accelerated Databases

On the programmability of multi-GPU computing systems

Efficient Kernel Fusion Techniques for Massive Video Data Analysis on GPGPUs

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

CRINK: Automatic CUDA code generation for affine C programs

Accelerating Protein Structure Prediction using Particle Swarm Optimization on GPU

On the use of deep Boltzmann machines for road signs classification

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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