Session ID: HKG18-312
Session Name: HKG18-312 - CMSIS-NN
Speaker: Rod Crawford
Track: LEG;Ecosystem Day
★ Session Summary ★
Deep learning algorithms are gaining popularity in IoT edge devices, because of their human-level accuracy in many applications, such as image classification and speech recognition. There is an increasing interest in deploying neural networks (NN) on always-on systems such as Arm Cortex-M microcontrollers. In this session, we introduce the challenges of deploying neural networks on microcontrollers with limited memory/compute resources and power budget. We introduce CMSIS-NN, optimized software kernels to enable deployment of neural networks on Cortex-M cores. We further present NN architecture exploration, using keyword spotting application as an example, to develop light-weight models suitable for resource constrained systems.
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★ Resources ★
Event Page: http://connect.linaro.org/resource/hkg18/hkg18-312/
Presentation: http://connect.linaro.org.s3.amazonaws.com/hkg18/presentations/hkg18-312.pdf
Video: http://connect.linaro.org.s3.amazonaws.com/hkg18/videos/hkg18-312.mp4
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★ Event Details ★
Linaro Connect Hong Kong 2018 (HKG18)
19-23 March 2018
Regal Airport Hotel Hong Kong
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Keyword: LEG;Ecosystem Day
'http://www.linaro.org'
'http://connect.linaro.org'
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