Embedded System Design and Synthesis. Transition. Evolution of computation. Two major sources of changing problems. Impact of scaling on delay

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Transition http://robertdick.org/esds/ Office: EECS 2417-E Department of Electrical Engineering and Computer Science University of Michigan Classes will transition from covering background on embedded systems to discussing recent papers, some of which are closely related to student projects. Discuss Joseph Polastre, Robert Szewczyk, Alan Mainwaring, David Culler, and John Anderson. Analysis of wireless sensor networks for habitat monitoring. In C. S. Raghavendra, Krishna M. Sivalingam, and Taieb Znati, editors, Wireless Sensor Networks, chapter 18, pages 399 423. Springer US, 2004. Practice exam. Impact of technology trends. 2 Two major sources of changing problems New implementation technologies. New applications. 1800s: Mechanical Late 1800s early 1900s: Electro-mechanical Early 1900s mid 1900s: Vacuum tube electronic Mid 1900s late 1900s: Bipolar (TTL) Late 1900s early 2000s: MOS 3 5 Impact of scaling on volume Impact of scaling on delay 6 7

Impact of scaling on energy consumption Impact of scaling on price 8 9 Scaling trends Device trends 10 11 Advantages of CMOS relative to prior technologies Current status for CMOS Performance Gain, low noise Area Massive integration Power Reliability Fabrication difficulty & cost 32 nm Power, thermal problems severe Fabrication cost per design high Potential reliability problems in future Soft errors Electromigration, dielectric breakdown, etc. Process variation Soon: Discrete dopant problems 12 13

Computing trends applications Advantages of alternative nanotechnologies Increased market volume and size for portable and embedded systems compared to general-purpose computers. May allow continued process scaling after CMOS scaling impractical. Instructor s opinion: Embedded will grow in importance in the future. Candidates High-performance general-purpose computing will still matter. Nanowire Single electron tunneling transistors Carbon nanotube Much of the general-purpose computation will move to data centers. 14 15 Comparison of nanoscale technologies Carbon Credit to ITRS 05 report on Emerging Research Devices. 16 18 CNT history CNT classes Graphene 19 20 Single-walled CNT Multi-walled CNT

Chirality Metallic and semiconducting CNTs Armchair (metallic) Zigzag (semi-conducting) 21 22 CNT properties Metallic or semiconducting. Diameter: 0.4 100 nm. Length: up to millimeters. Ballistic transport. Excellent thermal conductivity. Very high current density. High chemical stability. Robust to environment. Tensile strength: 45 TPa. Steel is 2 TPa. Temperature stability 2,800 in vacuum. 700 in air. 23 CNTs compared with Cu Property CNT Cu Max I dens. (A/cm 2 ) > 1 10 9 (Wei et al., APL 01) 1 10 7 Thermal cond. (W/mK) 5,800 (Hone et al., Phy Rev B 99) 385 Mean free path (nm) > 1, 000 (McEuen et al. T Nano 02) 40 24 NRAM Power challenges High-performance applications: energy cost, temperature, reliability Portable embedded systems: battery lifetime Uses Van der Waals forces. Non-volatile. SRAM-like speed. DRAM-like density. Ready for market in 2007 (and 2008, and 2009, and 2010, and 2011). IEEE Spectrum loser of the year. Why? 25 Power(W) 1000 100 10 Intel 386 Intel 486 Intel pentium Intel pentium2 Intel pentium3 Intel pentium4 Intel itanium Alpha 21064 Alpha 21164 Alpha 21264 Spar c Super Spar C Spar c64 Mips HP PA Power PC AMD K6 AMD K7 AMD x86-64 AMD Athlon64X2 AMD Barcelona Intel Clovetown Sun Niagara Sun Niagara 2 1 1985 1990 1995 2000 2005 2010 Year 27

Vacuum IBM 360 Fujitsu VP2000 IBM 3090S NTT Fujitsu M-780 IBM 3090 CDC Cyber 205 IBM 4381 IBM 3081 Fujitsu M380 IBM RY5 IBM RY7 Pulsar IBM RY6 IBM RY4 Apache T-Rex Mckinley IBM GP Merced Squadrons Pentium 4 Pentium II(DSIP) What does history teach us about power consumption? Device innovations have been the most effective method Vacuum tube to semiconductor device in the 1960s Bipolar device to CMOS transistor in the 1990s Power density (Watts/cm 2 ) 14 12 10 8 6 4 2 0 IBM 370 IBM 3033 IBM ES9000 Bipolar 1950 1960 1970 1980 1990 2000 2010 Year of announcement CMOS Jayhawk(dual) Based on diagram by C. Johnson, IBM Server and Technology Group 28 Prescott IBM Z9 Single electron tunneling transistor structure Device structure Island, terminals (source, drain, gate) Electron tunneling through tunneling junctions island source (S) C S,R S gate (G) optional 2 nd gate (G 2 ) tunnel junction drain (D) C D,R D C G :gate capacitance C D :drain tunnel junction capacitance C G2 :optional 2 nd gate capacitance R S :source tunnel junction resistance C S :source tunnel junction capacitance R D :drain tunnel junction resistance 29 C G C G2 Single electron tunneling transistor behavior Physical principles Coulomb charging effect governs electron tunneling Coulomb blockade V GS = me/c G, m = ±1/2, ±3/2, OFF, m = 0, ±1, ±2, ON SET properties and challenges Ultra low power Projected energy per switching event (1 10 18 J) I DS (na) 10 1 0.1 0.01 NVC PVC Temperature: 5K Temperature: 10K Temperature: 20K Room temperature and fabrication challenge Electrostatic charging energy must be greater than thermal energy e 2 /C > k B T Requires e 2 /C > 10k B T or even e 2 /C > 40k B T 0.001-60 -40-20 0 20 40 60 80 V GS (mv) 30 31 SET properties and challenges Summary Performance challenge Electrons must be confined in the island R S, R D > h/e 2, h/e 2 = 25.8 kω High resistance, low driving strength Reliability concerns Tunneling between charge traps cause run-time errors Unknown before fabrication Device technology: Improved by silicon islands Reliable design: Post-fabrication adaptation Run-time error correction CMOS will be mainstream for years to come, but not forever. The meaning of integrated circuits will change in the future. Circuit and logic design fundamentals will still apply. Some rules, e.g., difficulty of implementing non linearly separable functions, may change. You will each need to adapt as the rules governing device behavior change, but this will be much faster now that you have a foundation. 32 33

Due 20 October: Mini-project report. Due 20 October: Joseph Polastre, Robert Szewczyk, Alan Mainwaring, David Culler, and John Anderson. Analysis of wireless sensor networks for habitat monitoring. In C. S. Raghavendra, Krishna M. Sivalingam, and Taieb Znati, editors, Wireless Sensor Networks, chapter 18, pages 399 423. Springer US, 2004. Due 25 October: Main project proposal. Due 25 October: Email me one paper that you have read when working on your project that you think might be of interest to the entire class. Due 25 October: Ben W. Cook, Steven Lanzisera, and Kristofer S. J. Pister. SoC issues for RF smart dust. Proc. IEEE, 94(6), June 2006. 35