Specially designed for the CAISA architecture, RainBuilder provides rapid deployment for deep learning algorithms in just two steps. It supports TensorFlow, Caffe, PyTorch, ONNX (Mxnet, PaddlePaddle) and most deep learning frameworks with a versatile and user-friendly developing environment.
Compatible with mainstream deep learning frameworks;
Enhanced automatic compiling network models;
Automatic quantitative compression, node fusion, memory optimization.
Simplifies development process;
Provides C ++ / Python API for expansion;
Provides performance model analysis, accuracy verification, automatic thread scheduling, etc.
Support CAISA hardware driver, software-hardware scheduling, and streaming graph analysis;
Straightforward, automatic performance optimization and scheduling.
Shenzhen | 14F, Changfu Jinmao Building(CFC), Trade-free Zone, Futian District, Shenzhen, Guangdong, China
UK | Kemp House,152-160 City Road, London, EC1V 2NX
Shanghai | Room C509, 5F, Building C, Hongqiao Wantong Center, No.333 Su Hong Road, Minhang District, Shanghai, China
Jinan | 14F, Building 3, Future Innovation Park, 3 Gangxing Road, Licheng District, Jinan, Shandong，China
Xi 'an | Room 1211, 12F, Building T1, Lai 'an Center, 1111 Yanta Road, Qujiang New District, Xi 'an, Shaanxi , China
Shenyang | Unit 064A, 6F, Huahang Building, 77 Wenhua Road, Heping District, Shenyang, Liaoning , China