Baidu PaddlePaddle and Ruixin micro compatibility certificate
In the age of AI, deep learning framework is similar to operating system, which plays a role of connecting the preceding and the following, connecting chips and applications. AI chip with powerful computing power will gain more popularity.
NPUTime comes hard and softcombinationperformanceoptimization
RSIC micro AI chips rk1808 and rk1806 have built-in independent NPU neural computing unit, with int8 computing power as high as 3.0tops; with 22nm fd-soi process, the power consumption under the same performance is about 30% lower than the mainstream 28nm process products, with excellent performance in computing power, performance, power consumption and other indicators. The test results show that mobilenet V1 in paddy Lite takes only 6.5 MS to run, and the frame rate is as high as 153.8 FPS.
Based on Baidu's years of in-depth learning technology research and industrial application, the open-source platform for in-depth learning of the propeller industry integrates core training and prediction framework, basic model library, end-to-end development kit, tool components and service platform. It was officially opened in 2016, and is an influential industry-level in-depth platform with comprehensive open source, leading technology and complete functions in China Learning platform. Paddy Lite is a set of lightweight reasoning engine with perfect function, strong usability and excellent performance, which supports a variety of hardware and platforms, and has important characteristics such as lightweight deployment and high-performance implementation.
Raytheon microRK18xxSerial chip adapts to paddy Lite
Raytheon microRK18xxSerial chips inMobileNETV1Top vs. mainstreamCPUExcellent performance
By adapting to the open-source deep learning platform of the flying oar, Ruixin microchip will be able to better meet the business needs of domestic users and provide strong computing power for the end-side AI; the integration of the two will give full play to the advantages of the combination of software and hardware, speed up the development and deployment, and promote the landing of more AI applications.
Refer to the file of paddy Lite for the detailed operation method of Ruixin micro AI chip on the flying oar, including the supported chips, equipment list, paddy model and operators, demonstration of reference examples, etc.
(search path: baidu searches "paddy Lite document", selects release-v2.6.0 in the lower left corner, and deploys the case section "paddy Lite uses rk NPU to predict deployment")
Test equipment（RK1808 EVB)
In addition, in addition to RK1808 and RK1806 chip solutions, Ruixin micro NPU's AI chip will also be upgraded to match Baidu PaddlePaddle, further deepen bilateral cooperation, and work together to help build our own controllable AI ecosystem.