Introduction to Embedded Systems Research: Course...

Introduction to Embedded Systems Research:Course Review

Robert Dick

[email protected] of Electrical Engineering and Computer Science

University of Michigan

1.1040

2.1041

385

2.1039

704

1.1039

36

2.1040

1734

0.1039

1

3.1040

4

4.1039

642

3.1039

4.1040

409

3.1041

396665

5.1042

108612774

5.1040

337

4.1041

10644

6.1044

117

6.1039

609

6.1045

164

6.1040

841434 723938

6.1042

209

5.1041

4 12 164

5.1045

529417

5.1044

140105 88

5.1039

154 10551 90677

7.1039

1248

7.1047

2106

7.1040

29773362 241966 22903106

6.1041

3119 1936 40

6.1047

4128 253

8.1050

4

8.1042

9.1050

24784

8.1039

89632

8.1044

2840

8.1040

1088

9.1039

10.1040

4

11.1039

957

10.1050

144

11.1040

156

10.1041

32 16

10.1047

87780

10.1045

2152

10.1039

1165

12.1040

145

13.1052

2404

12.1042

24

12.1045

33008

12.1044

8217

12.1041

8

12.1039

135427

14.1049

113

14.1040

229

13.1050

132

13.1042

74433

13.1041

17187

13.1040

2715

13.1039

170059 90

15.1040

16

15.1050

242 1225

14.1050

237

14.1042

6200

14.1041

4

14.1044

720

14.1052

20

14.1039

84 36939

16.1040

88

15.1049

6

15.1039

56

17.1054

2919

16.1050

129

16.1041

36

16.1047

49154

16.1045

2632

16.1049

27

16.1052

16

16.1039

222734

18.1048

133

18.1039

3439

18.1040

241

17.1050

16

18.1049

36 339224

17.1042

172832

17.1041

49620 448

17.1040

1376493 2883

17.1045

72

17.1044

1073

17.1049

55441826

17.1048

124 3648290

17.1052

3547

17.1039

2484110477445

17.1047

24

19.1040

72

19.1039

6 88 60631617

18.1041

28 76

18.1047

3305

18.1054

13744

20.1040

109

20.1039

269

19.1052

8

19.1047

11712

19.1049

10

19.1054

7520

21.1039

82

20.1049

5

20.1047

4896

20.1054

864

22.1040

4

22.1050

23.1040

4

22.1039

144

24.1058

3389

23.1050

76

24.1040

4

23.1042

17528

23.1041

4

23.1054

24

23.1044

6234

23.1058

261

23.1049

4

23.1052

2944

23.1039

3069658

25.1040

80

24.1050

4

24.1039

58

25.1039

26.1040

4

27.1039

489

26.1050

4

27.1040

4

26.1047

3808

26.1045

2248

26.1058

113 80

26.1049

11

26.1039

66

26.1054

840

28.1055

84266 1542

27.1042

1229

27.1041

29619

27.1058

12

27.1049

3984

27.1048

35337

29.1040

262

29.1056

164

29.1039

742

28.1050

4 2464

28.1042

2137912

29.1055

1128

28.1041

4 2633 4

28.1040

2716132 691

28.1058

24 84 32

28.1049

36176 3

28.1048

1192 48

28.1039

365 110957 24475

29.105029.104229.104129.104729.104529.105829.104929.105229.1054

2

3

4

5

6

7

8

0 1 2 3 4 5 6 7 8

Pow

er

(mW

)

Time (s)

35 40 45 50 55 60 65 70 75 80 85 90

-8 -6 -4 -2 0 2 4 6 8

-8

-6

-4

-2

0

2

4

6

8

35 40 45 50 55 60 65 70 75 80 85 90

Temperature (°C)

Position (mm)

Temperature (°C)

OverviewPre-Midterm

Post-MidtermAdvising offer

Outline

1. Overview

2. Pre-Midterm

3. Post-Midterm

4. Advising offer

2 R. Dick EECS 598-13

OverviewPre-Midterm


What I am attempting to rate

Do you have a broad understanding of research topics and ideas connectedto embedded system analysis, design, and implementation?

Do you have a deep understanding of the challenges facing IoT systems andhow they relate to using machine learning techniques for analysis anddecision making?


OverviewPre-Midterm


How I will rate these things

2/3–3/4 of questions will be on post-midterm topics.

Around 2/3 of questions will be high-level, e.g., did you understand the mainnew idea in a particular paper?

Around 1/3 of questions will be more detailed and may require somecalculation, although algebra will generally be sufficient for most of these.


OverviewPre-Midterm


Placing out

I may conclude that there is sufficient evidence to assign grades to somestudents without a final exam.

If you are one of these students, I will contact you. You will have the optionto accept the proposed grade or take the final, in which case the final will beweighted in appropriately.


How to study

Lectures

Review all the lecture notes.

Review video sections on topics you don’t remember well.

Papers

Do you understand the main new ideas in the paper?

Read your summaries of all papers.

Skim the summaries of two other students.

Use Piazza to discuss ambiguous concepts.

I will check Piazza frequently until the exam.

Projects

Goal, challenges, ideas, and results (did it work?).

Read your notes on student presentations, or read their slides.

Watch videos for topics that aren’t clearly explained in the slides.

OverviewPre-Midterm


Outline

1. Overview

2. Pre-Midterm

3. Post-Midterm

4. Advising offer


OverviewPre-Midterm


Topics I

Application trends.

Technology trends.

Costs and constraints.

Specification languages and models.

Allocation, assignment, and scheduling.

Memory hierarchies.

Embedded and real-time operating systems.

Sensors and actuators.

Wireless power transfer applications.


OverviewPre-Midterm


Topics II

Cyberphysical systems.

Energy- and temperature-aware low-power design and power modeling.

Wireless communication and its impact on power consumption.

Reliability-aware design and formal methods.

A little bit of material on testing.

Embedded system security.

Smartphones.

Wireless sensor networks.


OverviewPre-Midterm


Outline

1. Overview

2. Pre-Midterm

3. Post-Midterm

4. Advising offer


OverviewPre-Midterm


Topics I

Wearables.

Autonomous vehicles.

Embedded vision applications.

Communication, machine learning, and energy efficiency in theInternet-of-Things.

Energy-efficient machine learning algorithms: pruning, BNNs, weightcompression, etc.

Energy-efficient machine learning hardware.

LPWANs.

Devices for machine learning.


OverviewPre-Midterm


Topics II

Reliability, security, and privacy in the Internet-of-Things.

Vision in the Internet-of-Things.


OverviewPre-Midterm


Student projects

Evolving PCB antennas.

Sensing pollinators.

Analysis of Bluetooth mesh network.

Incentivizing message forwarding in delay-/defect-tolerant networks.

Modified base delta L1 cache compression.

Long-range LoRa.

Signal processing pipeline auto-calibration.

Scene cache for energy-efficient machine vision.


OverviewPre-Midterm


Papers I

S. A. Edwards, “Design and verification languages,” Columbia University,Tech. Rep., Nov. 2004.

L. Yang, R. P. Dick, H. Lekatsas, and S. Chakradhar, “High-performanceoperating system controlled on-line memory compression,” ACM Trans.Embedded Computing Systems, vol. 9, no. 4, pp. 30:1–30:28, Mar. 2010.

R. I. Davis and A. Burns, “A survey of hard real-time scheduling formultiprocessor systems,” ACM Computing Surveys, vol. 43, no. 4, Oct. 2011.

E. A. Lee, “The past, present and future of cyber-physical systems: A focuson models,” Sensors, Feb. 2015.


http://robertdick.org/publications/yang10mar.html

http://robertdick.org/publications/yang10mar.html

OverviewPre-Midterm


Papers II

A. P. Sample, D. J. Yeager, P. S. Powledge, A. V. Mamishev, and J. R.Smith, “Design of an rfid-based battery-free programmable sensingplatform,” IEEE Trans. on Instrumentation and Measurement, vol. 57,no. 11, pp. 2608–2615, Nov. 2008.

L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. P. Dick, Z. M. Mao, and L.Yang, “Accurate online power estimation and automatic battery behaviorbased power model generation for smartphones,” in Proc. Int. Conf.Hardware/Software Codesign and System Synthesis, Oct. 2010, pp. 105–114.

W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficientcommunication protocol for wireless microsensor networks,” in Proc. HawiiInt. Conf. on System Sciences, 2000.


http://robertdick.org/publications/zhang10oct.html

http://robertdick.org/publications/zhang10oct.html

OverviewPre-Midterm


Papers III

D. Zhu, R. Melhem, and D. Mosse, “The effects of energy management onreliability in real-time embedded systems,” in Proc. Int. Conf.Computer-Aided Design, Nov. 2004.

T. Trippel, O. Weisse, W. Xu, P. Honeyman, and K. Fu, “WALNUT: Wagingdoubt on the integrity of MEMS accelerometers with acoustic injectionattacks,” in Proc. European Symp. on Security and Privacy, Apr. 2017.

J. Polastre, R. Szewczyk, A. Mainwaring, D. Culler, and J. Anderson,“Analysis of wireless sensor networks for habitat monitoring,” in WirelessSensor Networks, C. S. Raghavendra, K. M. Sivalingam, and T. Znati, Eds.Springer US, 2004, ch. 18, pp. 399–423.

D. Cruz, J. McClintock, B. Perteet, O. A. A. Orqueda, Y. Cao, andR. Fierro, “A multivehicle platform for research in networked embeddedsystems,” IEEE Control Systems Magazine, June 2007.


OverviewPre-Midterm


Papers IV

C. Farabet, B. Martini, B. Corda, P. Akselrod, E. Culurciello, , andY. LeCun, “NeuFlow: A runtime reconfigurable dataflow processor forvision,” in Proc. Conf. Computer Vision and Pattern Recognition, June 2011.

B. Widrow and M. A. Lehr, “30 years of adaptive neural networks:Perceptron, madaline, and backpropagation,” Proc. IEEE, vol. 78, no. 9,Sept. 1990.

V. Sze, Y.-H. Chen, T.-J. Yang, and J. Emer, “Efficient processing of deepneural networks: A tutorial and survey,” Proc. IEEE, vol. 105, no. 12, Dec.2017.

S. Han, X. Liu, H. Mao, J. Pu, A. Pedram, M. A. Horowitz, and W. J. Dally,“EIE: Efficient inference engine on compressed deep neural network,” inProc. Int. Symp. Computer Architecture, June 2016.


OverviewPre-Midterm


Papers V

A. S. Cassidy et al., “Real-time scalable cortical computing at 46giga-synaptic OPS/Watt with 100x speedup in time-to-solution and100,000x reduction in energy-to-solution,” in Proc. Int. Conf. HighPerformance Computing, Networking, Storage and Analysis, Nov. 2014.

P. Coussy, C. Chavet, H. Wouafo, and L. Conde-Canecia, “Fully binaryneural network model and optimized hardware architectures for associativememories,” ACM J. on Emerging Technologies in Computing Systems,vol. 11, no. 4, Apr. 2015.

U. Raza, P. Kulkarni, and M. Sooriyabandara, “Low power wide areanetworks: An overview,” IEEE Communications Surveys and Tutorials,vol. 19, no. 2, May 2017.


OverviewPre-Midterm


Papers VI

P. M. Sheridan, F. Cai, C. Du, W. Ma, Z. Zhang, and W. D. Lu, “Sparsecoding with memristor networks,” Nature Nanotechnology, vol. 12, Aug.2017.

E. Ronen, A. Shamir, A.-O. Weingarten, and C. O’Flynn, “IoT goes nuclear:Creating a ZigBee chain reaction,” in Proc. Symp. on Security and Privacy,May 2017.

Y. Zhu, A. Samajdar, M. Mattina, and P. Whatmough, “Euphrates:Algorithm-SoC co-design for low-power mobile continuous vision,” arXiv,Tech. Rep., Apr. 2018.


OverviewPre-Midterm


Outline

1. Overview

2. Pre-Midterm

3. Post-Midterm

4. Advising offer


OverviewPre-Midterm


Advising

Research, product design, or career options.

Group discussion.


Introduction to Embedded Systems Research: Course...

Documents

Transcript of Introduction to Embedded Systems Research: Course...