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Using DRBL to Deploy MPICH2 and CUDA on Green Computing

Wu Jiun-Yu, Wang Yao-Tsung, Shiau Steven, Wang Hui Ching

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Tags: Computer science, CUDA, Energy-efficient computing, Green, nVidia, nVidia GeForce 9800 GT

November 1, 2011 by hgpu

Power Management and Optimization

Hari Sundararajan

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Tags: Computer science, CUDA, Energy-efficient computing, Green, nVidia, nVidia GeForce GTX 260, Performance, Thesis

October 2, 2011 by hgpu

Optimizing a Semantic Comparator using CUDA-enabled Graphics Hardware

Aalap Tripathy, Suneil Mohan, Rabi Mahapatra

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Tags: Bloom filter, Computer science, CUDA, Green, Hashing, nVidia, Semantic indexing, Tesla C870

October 1, 2011 by hgpu

Energy-efficient algorithms

Susanne Albers

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Tags: Algorithms, Computer science, Energy-efficient computing, Green, Review

February 11, 2011 by hgpu

A first look at integrated GPUs for green high-performance computing

T. Scogland, H. Lin, W. Feng

Tags: Computer science, Embedded high-performance computing, Energy-efficient computing, Green, Performance

November 2, 2010 by hgpu

Neural Query Language: A Knowledge Base Query Language for Tensorflow

Neural Query Language: A Knowledge Base Query Language for Tensorflow

NMODL: Code Generation Framework For NEURON MODeling Language

An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language

TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox

cuda-benches: collection of small CUDA benchmarking programs

Performance Engineering for a Tall & Skinny Matrix Multiplication Kernel on GPUs

Simulee: Charactering and Detecting CUDA Program Bugs

Charactering and Detecting CUDA Program Bugs

TensorNetwork: A TensorFlow library for easy and efficient manipulation of tensor networks

TensorNetwork: A Library for Physics and Machine Learning

jive

Principles, Techniques, and Tools for Explicit and Automatic Parallelization

caffe-mc-opencl: Caffe Deep Learning Software with Model Compression by Sparse Coding (Backend: OpenCL)

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Full-stack Optimization for Accelerating CNNs with FPGA Validation

Full-stack Optimization for Accelerating CNNs with FPGA Validation

AdaNet: Fast and flexible AutoML with learning guarantees

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

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2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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