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Issue Topics

2003 May Issue 3

RLE Pursues the Optical Clock
Erich P. Ippen at the New Limits of Precision

Multidisciplinary Initiative
the DoD MURI program and RLE

Rising Stars
Oxenham and Sugiyama

Students at the Forefront
The Helen Carr Peake Research Prize

Computational Prototyping
an interview with Jacob K. White

Introducing a New Professor
Luca Daniel joins RLE

Download PDF of Issue 3


 

INSPIRED ELECTRONICS:
an interview with Rahul Sarpeshkar
(this is an expanded version of the interview appearing in the print copy of RLE at MIT)
2002 December Issue 1

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RLE: What does the term "biologically inspired electronics" mean?
Sarpeshkar: "Biologically inspired" electronics refers to electronics whose design is inspired by architectures or organizing principles seen in biological systems. For example, a "silicon cochlea" design is inspired by the traveling-wave architecture of the human inner ear or cochlea, a "Reichardt motion sensor" is inspired by correlation motion circuits in insect eyes, and a "biosonar front end" is inspired by signal processing in the bat or dolphin. My research inspiration comes primarily from neurobiological systems.

WHAT IS HYBRID COMPUTING? Digital computation uses all-black or all-white signal representatives to compute while analog computation uses the continuous shades of gray in between black and white as well. Digital computation functions with all technologicaRLE: What are the features of neurobiological systems that indicate possibilities for fundamentally new generations of devices?
Sarpeshkar: Neurobiological systems perform complex sensory and sensorimotor tasks in real time, with very low power, and in a very small volume. For example, the human inner ear does at least a GFLOP of computation in a volume that is less than 40 mm^3, and with a power consumption that would allow operation on a AA battery for 15 years. Such incredible specifications are attained because of a clever use of technology for computation (fluid mechanics, micromechanics, and microelectronics in the case of the ear), and through efficient nonlinear, adaptive, and distributed architectures. Designs that insightfully mimic biological structures hold great promise for ultra low power electronics, for feedback system design, and for revolutionary computational architectures.

RLE: Why does hybrid computing hold potential for dramatic power efficiency improvements in signal processors?
Sarpeshkar: Hybrid computing attempts to combine the analog advantages of low power operation and superior exploitation of the technology with the digital advantages of signal restoration, divide-and-conquer processing, scalability, and programmability. Since such a computational paradigm combines the best of the analog and digital worlds, dramatic power-efficiency improvements may be possible

RLE: Why are such efficiency improvements important for radically new types of electronic devices and systems?
Sarpeshkar: Power efficiency improvements are important in portable systems, which need to compute in a small lightweight volume on modest amounts of battery power. Cell phones, laptop computers, medical implants in the human body, wireless sensors, spacecraft, and mobile robots are all examples of such devices. Many people believe that the explosive demand for such devices will continue into the future and spawn applications that we have not yet imagined. Power efficiency is also extremely important in the scalability of future microprocessors to smaller channel lengths

RLE: What does your groupís recent success exploiting the hybrid computing approach to develop integrated circuits that mimic neurological processes of the brain suggest for the future?
Sarpeshkar: I believe that the brain is the worldís greatest hybrid computer. It uses ìspikesî or pulses to compute, which have an inherently hybrid nature: the time between pulses is a continuous analog variable while the pulses themselves are all-or-none discrete events. My lab is researching the use of such time-based signal representations to perform ultra-low-power analog-to-digital conversion, to build analog memories, to build hybrid computers specialized for processing sensory data, and to build novel event-based hybrid control architectures.

RLE: What are the most difficult problems today facing scientists in attempting to recreate the capabilities of biological systems in man-made devices and systems?
Sarpeshkar: The most difficult problems lie in three areas. First, understanding how to perform efficient-and-reliable computations with noisy and unreliable physical devices, a feat that neurobiological systems perform routinely without treating all computing devices as switches. Second, understanding the design, performance, and robustness of distributed control architectures that operate at multiple temporal and spatial scales. Third, advancing technology to a point where we may begin to replicate the high fan in and fan out capabilities of low-power, slow-and-parallel architectures such as the brain, or to the point where we can combine various technologies on one integrated substrate as in the human ear.

 

 

 
Additional Links
Professor Rahul Sarpeshkar


Rahul Sarpeshkar has just been named the Robert J. Shillman Career Development Professor of Electrical Engineering and Computer Science. Sarpeshkar is the first holder of this professorship, which was created by Dr. Robert J. Shillman, an alumnus of RLE. Shillman is founder and president of Cognex Corporation, a world leader in machine vision systems. Like his RLE colleague Wolfgang Ketterle, Sarpeshkar is a winner of the prestigious David and Lucille Packard Fellowship in Science and Engineering.

Sarpeshkar has directed RLE's Analog VLSI and Biological Systems Group since joining the MIT faculty in 1999. His research team has achieved major advances in our understanding of low-power analog very large scale integrated (VLSI) systems. Central to Sarpeshkar's approach is looking to biology to uncover fundamental clues that could inform the design of a new generation of electronics.

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