PaddlePaddle (PArallel Distributed Deep LEarning) is an easy-to-use, efficient, flexible and scalable deep learning platform, which is originally developed by Baidu scientists and engineers for the purpose of applying deep learning to many products at Baidu. Features include: a) Ease of use - PaddlePaddle is designed to be easy to use. It provides an intuitive and yet flexible interface for loading data and specifying model structure; b) Flexibility - PaddlePaddle supports a wide range of neural network architectures and optimization algorithms. It is easy to configure complex models such as neural machine translation model with attention mechanism or complex memory connection; c) Efficiency - In order to unleash the power of heterogeneous computing resource, optimization occurs at different levels of PaddlePaddle, including computing, memory, architecture and communication.; and d) Scalability - With PaddlePaddle, it is easy to use many CPUs/GPUs and machines to speed up your training. PaddlePaddle can achieve high throughput and performance via optimized communication. This will be added to the tools section of Research Resources Subject Tracer™. This will be added to Entrepreneurial Resources Subject Tracer™.
posted by Marcus Zillman |
1:28 AM
