Tags : Browse Projects

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landscapes-svo

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  Analyzed about 19 hours ago

Sparse Voxel Octree implementation

12.4K lines of code

0 current contributors

over 8 years since last commit

0 users on Open Hub

Inactive
0.0
 
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corner-cases

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  Analyzed 1 day ago

A library for reasoning about a cube, the faces, corners, and edges of a cube.

7.57K lines of code

0 current contributors

about 8 years since last commit

0 users on Open Hub

Inactive
0.0
 
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CLRadeonExtender

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  No analysis available

This project is low-level development tools (assembler, disassembler) for Radeon GPU's. Only Radeon with GCN architecture will be supported.

0 lines of code

1 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: GNU_Free_..., GNU-GPLv2, LGPLv2_1

Autumn Leaf

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  Analyzed about 14 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
 
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aparapi

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  Analyzed about 17 hours ago

API for data parallel Java. Allows suitable code to be executed on GPU via OpenCL.

234K lines of code

0 current contributors

over 7 years since last commit

0 users on Open Hub

Inactive
0.0
 
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Licenses: No declared licenses

DiabloMiner

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  Analyzed about 2 hours ago

OpenCL miner for BitCoin

1.93K lines of code

0 current contributors

7 months since last commit

0 users on Open Hub

Very Low Activity
0.0
 
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veles

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  Analyzed about 3 hours 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
0.0
 
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node-cello

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  Analyzed 34 minutes ago

Simple DSL for generating C programs

1.1K lines of code

0 current contributors

almost 11 years since last commit

0 users on Open Hub

Inactive
0.0
 
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rcl

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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
0.0
 
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Mostly written in language not available
Licenses: gpl3

incubator-singa

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  Analyzed about 10 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]

88.3K lines of code

28 current contributors

2 days since last commit

0 users on Open Hub

Moderate Activity
0.0
 
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