Internet of Smart Things

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1 Advanced Research Intelligent Embedded Systems Politecnico di Milano Internet of Smart Things where machine learning meets embedded systems Prof. Manuel Roveri Dipartimento di Elettronica, Informazione e Bioingegneria Politecnico di Milano

2 Computer science and AI: the rise of both disciplines Claude Shannon ( ) Alan Turing ( ) Stand on the shoulders of Giants

3 Computer science and AI: the rise of both disciplines A B C Claude Shannon ( ) A Symbolic Analysis of Relay and Switching Circuits, Master's degree thesis, Massachusetts Institute of Technology, 1937

4 Computer science and AI: the rise of both disciplines A= Fever B= Flu ill Stay at home C= Night Claude Shannon ( ) A Symbolic Analysis of Relay and Switching Circuits, Master's degree thesis, Massachusetts Institute of Technology, 1937

5 Computer science and AI: the rise of both disciplines Garry Kasparov (2012) playing Turing s Chess (1948) TURING TEST A test for a machine to be called "intelligent Alan Turing ( )

6 Computer science and AI: the rise of both disciplines Garry Kasparov (2012) playing Turing s Chess (1948) TURING TEST A test for a machine to be called "intelligent Alan Turing ( )

7 Generations and seasons Univac Eniac Transistor Integrated Circuits Microprocessors Statisitcal Methods 1945 Pioneering works in the field of AI Bayesian Inference Neural Networks Today K Nearest Neighbour BackProp SVM Deep Learning

8 Generations and seasons: the evolution of computation and memory Univac Computational Power Available Memory Eniac Transistor Integrated Circuits Microprocessors Statisitcal Methods 1945 Pioneering works in the field of AI Bayesian Inference Neural Networks Today K Nearest Neighbour BackProp SVM Deep Learning Computational needs Memory Requirements

9 AI and Technology RAM 50x 100x 1Kx 10Kx GPU, FPGA Neural HW Supercomputers HPC x x Embedded PCs PC 0.1x 0.5x 20x 50x 100x 1000x Computation Speedup Embedded Systems 0.01x 0.05x

10 AI and Technology RAM 50x 100x 1Kx 10Kx GPU, GPUs, FPGA Neural HW Supercomputers Supercomputers (Systems of GPUSs HPC or Neural HWs) Deep Learning x x Embedded PCs PC 0.1x 0.5x 20x 50x 100x 1000x Computation Speedup Embedded Systems Intelligent Cyber-Physical Systems 0.01x 0.05x

11 Intelligent Internet-of-Things and Cyber-Physical Systems Cyber Domain Adaptation Intelligent Processing of Physical Sensing Intelligent IoT and Cyber- Physical Systems Cognitive Mechanisms for Actuation and Control Reliability Selfawareness Self- Diagnosis Physical Domain Selfhealing

12 POLIMI and STMicroelectronics: Designing Intelligent Cyber-Physical Systems

13 The Intelligent Embedded Sensors: learning Recurrent Neural Networks (ESNs) Trained on a Coordinatorof the CPS Trained on the Intelligent Embedded Sensor

14 The Intelligent Embedded Sensors: robustness mechanisms to shield removal Self- ability to manage the removal and the insertion of the sensor shield board from the STM32 main board

15 The Coordinator: dependency-graph learning and network management

16 The Server: data analysis, processing and visualization

17 The Testbed: Intelligent Monitoring of Datacenters

18 What about Deep Learning? RAM 50x 100x 1Kx 10Kx GPUs, Neural HW Supercomputers (Systems of GPUSs or Neural HWs) Deep Learning x x 0.05x 0.1x Embedded PC PC 0.1x 0.5x 20x 50x 100x 1000x Computation Speedup Embedded Systems 0.01x 0.05x

19 What about Deep Learning? RAM 50x 100x 1Kx 10Kx Deep Learning x x 0.05x 0.1x PC 20x 50x 100x 1000x Embedded Systems 0.1x 0.5x Computation Speedup Embedded Systems 0.01x 0.05x

20 How to meet Embedded Systems with Deep Learning? RAM Re-design of the CNN architecture Approximate Computing 50x 100x 1Kx 10Kx Embedded System Code x x Optimization 0.05x 0.1x PC 20x 50x 100x 1000x 0.1x 0.5x Computation Speedup Embedded Systems 0.01x 0.05x

21 Progetto Regione Lombardia - Smart Living ( ) S istema I ntelligente per il M onitoraggio e la P redizione della S olidità St rutturale di edifici e infrastrutture e per la pianificazione dell intervento - SIMPSS

22 Thank you for the attention!