Implementing Neural Networks Efficiently
| Type of publication: | Book chapter |
| Citation: | Collobert_SPRINGER_2012 |
| Booktitle: | Neural Networks: Tricks of the Trade |
| Edition: | Second |
| Year: | 2012 |
| Publisher: | Springer |
| Abstract: | Neural networks and machine learning algorithms in general require a flexible environment where new algorithm prototypes and experiments can be set up as quickly as possible with best possible computational performance. To that end, we provide a new framework called Torch7, that is especially suited to achieve both of these competing goals. Torch7 is a versatile numeric computing framework and machine learning library that extends a very lightweight and powerful programming language Lua. Its goal is to provide a flexible environment to design, train and deploy learning machines. Flexibility is obtained via Lua, an extremely lightweight scripting language. High performance is obtained via efficient OpenMP/SSE and CUDA implementations of low-level numeric routines. Torch7 can also easily be interfaced to third-party software thanks to Lua’s light C interface. |
| Keywords: | machine-learning software |
| Projects: |
Idiap |
| Authors: | |
| Editors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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