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cf4ocl

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  Analyzed about 21 hours ago

The C Framework for OpenCL, cf4ocl, is a cross-platform pure C99 object-oriented framework for developing and benchmarking OpenCL projects in C/C++.

29.5K lines of code

1 current contributors

4 months since last commit

0 users on Open Hub

Very Low Activity
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Mostly written in C
Licenses: gpl3, lgpl3
Tags accelerator c cpu gpu gpucomputing gpuprogramming library opencl parallelcomputing

GSvit

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  Analyzed about 18 hours ago

Fast FDTD solver with graphics card support. Optimized for nanoscale optics - scanning near field optical microscopy, rough surface scattering and solar cells. Uses CUDA environment for graphics card operation.

51.9K lines of code

0 current contributors

5 months since last commit

0 users on Open Hub

Very Low Activity
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Mostly written in C
Licenses: GPL2
Tags c computation cuda fdtd gpu gtk+ microscopy physics science simulation

cl_ops

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  Analyzed 1 day ago

A library of common OpenCL operations.

3.64K lines of code

0 current contributors

over 7 years since last commit

0 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in C
Licenses: gpl3, lgpl-v3
Tags cpu gpu gpucomputing gpuprogramming library opencl parallelprogramming prng randomnumbergenerator scientificcomputing sorting

biomanycores

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  No analysis available

Repository of open-source parallel bioinformatics code

0 lines of code

0 current contributors

0 since last commit

0 users on Open Hub

Activity Not Available
0.0
 
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Mostly written in language not available
Licenses: artistic, Biopython..., lgpl21_or...
Tags bioinformatics biojava bioperl biopython gpu

nervana_neon

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  Analyzed about 21 hours ago

Nervana's python based Deep Learning Framework

49.7K lines of code

4 current contributors

almost 5 years since last commit

0 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in Python
Licenses: No declared licenses
Tags cnn convolutional_networks gpu python recurrent_networks rnn

DMLC Minerva

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  Analyzed about 23 hours ago

Minerva: a fast and flexible tool for deep learning on multi-GPU. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy.

185K lines of code

0 current contributors

over 8 years since last commit

0 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in C++
Licenses: apache_2
Tags ann c++ cpu deep_learning gpu machine_learning multi-gpu ndarray neural_networks numpy python

Autumn Leaf

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  Analyzed about 7 hours ago

The Hacker's Machine Intelligence Framework engineered by software developers, not scientists. Leaf is portable. Run it on CPUs, GPUs, FPGAs on machines with an OS or on machines without one. Run it with OpenCL or CUDA. Credit goes to Collenchyma and Rust. Leaf is part of the Autumn Machine ... [More] Intelligence Platform, which is working on making AI algorithms 100x more computational efficient. Bringing real-time, offline AI to smartphones and embedded devices. Core for high-performance machine intelligence applications. Leafs' design makes it easy to publish independent modules to make e.g. deep reinforcement learning, visualization and monitoring, network distribution, automated preprocessing or scaleable production deployment easily accessible for everyone. [Less]

7.31K lines of code

0 current contributors

over 6 years since last commit

0 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in Rust
Licenses: apache_v2, mit
Tags cpu cross-platform cuda deep_learning embedded fpga gpu machine_learning neural_networks offline opencl real-time 2 more...

veles

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  Analyzed 1 day ago

Distributed machine learning platform. Distributed platform for rapid Deep learning application development Consists of: Platform - https://github.com/Samsung/veles Znicz Plugin - Neural Network engine Mastodon - Veles Java bridge for Hadoop etc. SoundFeatureExtraction - audio feature ... [More] extraction library Written on Python, uses OpenCL or CUDA, employs Flow-Based Programming, under Apache 2.0. 1 Deploy VELES on Notebook or Cluster with a single command 2 Create the model from >250 optimized units 3 Analyze and serve the dataset on the go using Loaders 4 Train it on PC or High Performance Cluster Interactively monitor the training process 5 Publish the results 6 Automatically extract the trained model as an application 7 Run it in the cloud [Less]

68.8K lines of code

0 current contributors

5 months since last commit

0 users on Open Hub

Very Low Activity
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0 Reviews
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Mostly written in Python
Licenses: apache_2
Tags cloud cluster cuda deployment distributed gpu hadoop hpc neural_networks opencl production python 1 more...

incubator-singa

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  Analyzed about 3 hours ago

SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. It is designed with an intuitive programming model based on the layer abstraction. A variety of popular deep learning models are supported, namely feed-forward models including ... [More] convolutional neural networks (CNN), energy models like restricted Boltzmann machine (RBM), and recurrent neural networks (RNN). Many built-in layers are provided for users. SINGA architecture is sufficiently flexible to run synchronous, asynchronous and hybrid training frameworks. SINGA also supports different neural net partitioning schemes to parallelize the training of large models, namely partitioning on batch dimension, feature dimension or hybrid partitioning. [Less]

87.6K lines of code

28 current contributors

about 1 month since last commit

0 users on Open Hub

Moderate Activity
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0 Reviews
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Mostly written in C++
Licenses: apache_2
Tags artificial_neural_networks cluster CNN CUDA cudnn deep_learning distributed gpu large_datasets large_scale machine_learning multiple_gpu 5 more...

Think Silicon

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  No analysis available

0 lines of code

0 current contributors

0 since last commit

0 users on Open Hub

Activity Not Available
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Mostly written in language not available
Licenses: No declared licenses
Tags 2dgraphics 3dgraphics embedded fpga gpgpu gpu graphics hardware opencl opengl