tinyML Talks: CMSIS-NN &Optimizations for Edge AI

Date

February 8, 2021

Location

Virtual

Contact us

Discussion

Schedule

Timezone: PDT

CMSIS-NN &Optimizations for Edge AI

Felix JOHNNY, Staff engineer

Arm

The talk is centered around performance optimizations for Edge AI applications. We’ll begin with identifying bottlenecks in the inference of ML models and move on to ways to handle them. A major part of the solution is in the use of a specialized library like CMSIS-NN which provides optimization for compute-intensive operators targeting Arm Cortex-M processors. Common optimization methodologies used in CMSIS-NN will also be discussed. We have something for model designers by showing how shapes of operators affect performance and some solutions to handle it.
In the end, Fredrik will give a live demo of CMSIS-NN together with TensorFlow Lite for Microcontrollers showcasing the benefits of optimization using an Arduino Nano 33 BLE sense board.

Fredrik KNUTSSON, Technical Lead

Arm

The talk is centered around performance optimizations for Edge AI applications. We’ll begin with identifying bottlenecks in the inference of ML models and move on to ways to handle them. A major part of the solution is in the use of a specialized library like CMSIS-NN which provides optimization for compute-intensive operators targeting Arm Cortex-M processors. Common optimization methodologies used in CMSIS-NN will also be discussed. We have something for model designers by showing how shapes of operators affect performance and some solutions to handle it.
In the end, Fredrik will give a live demo of CMSIS-NN together with TensorFlow Lite for Microcontrollers showcasing the benefits of optimization using an Arduino Nano 33 BLE sense board.

Felix JOHNNY, Staff engineer

Arm

Felix Johnny is the maintainer of Arm’s open source CMSIS-NN library that targets optimized Neural Network kernels for Cortex-M CPUs. He has spent most of the last 15 years in the wireless domain working with software design and optimizations in memory and cycle constrained systems. Outside of work, he is an active music photographer.

Fredrik KNUTSSON, Technical Lead

Arm

Fredrik Knutsson is the technical lead for the Arm team working on Ethos-U55 and Cortex-M integration into embedded runtimes. He holds a M.Sc. in electrical engineering from Chalmers university of technology. Fredrik has more than 15 years of experience in the embedded software domain, doing mainly software architecture and system design. Four the past four years he’s been working for Arm and has previous experience from the wireless, wearable and automotive business.

Schedule subject to change without notice.