I was invited to give a talk on my Research at the Royal Academy of Engineering event, held in Newcastle on the 28th January 2019.

The title of the talk is “Asynchronous Design Research or Building Little Clockless Universes”

The PDF of the slides of my talk are here: http://async.org.uk/presentations/AlexYakovlev-Research-RAEngEvent-280119.pdf

I only had 15 minutes give to me. Not a lot to talk about the 40 years of research life. So, at some point in preparing for this talk, I decided that I’ll try to explain what the research in microelectronic systems design is about, and in particular how my research in asynchronous design helps it.

Basically, I tried to emphasize on the role of ‘time control’ in designing ‘little universes’, where the time span covered by our knowledge of what’s is going on in those systems and why is between 1 few picoseconds (transistor switching event) and hours if not days (applications life times). So we cover around 10^18 events. How does it compare to the life of universe – being “only” around 10^13 years. Are we as powerful as gods in creating our ‘little universes’.

So, in my research I want to better control TIME at the smallest possible scale, surprisingly but, by going CLOCK-LESS! Clocking creates an illusory notion of determinacy in tracking events and their causal-relationship. Actually, it obscures such information. Instead by doing your circuit design in a disciplined way, such as speed-independent circuit design, you can control timing of events down to the best levels of granularity. In my research I achieved that level of granularity for TIME. It took me some 40 years!

But, furthermore, more recently, say in the last 10 years, I have managed to learn pretty well how to manage power and energy also to that smallest possible level, and actually make sure that energy consumption is known to the level of events controlled in a causal way. Energy/power-modulated computing, and its particular form of power-proportional computing, is the way for that. We can really keep track of where energy goes down to the level of a few femto-Joules. Indeed if a parasitic capacitance of an inverter output in modern CMOS technology is around 10fF and we switch it at Vdd=1V, we are talking about minimum energy quantity of CV^2=10fJ= 10^-14J per charging/discharging cycle (0-1-0 in terms of logic levels). Mobile phones run applications that can consume energy at the level of 10^4J. Again, like with time we seem to be pretty well informed about what’s going on in terms of energy covering 10^18 events! Probably, I’ll just need another 5 or so years to conquer determinacy in energy and power terms – our work on Real-Power Computing is in this direction.

Now, what’s next, you might ask? what other granularification, distribution and decentralization can we conquer in terms of building little universes!? The immediate guess that comes to my mind is the distribution (in time and energy directions) of functionality, and to be more precise intelligence. Can we create the granules of intelligence at the smallest possible scale, and cover same orders of magnitude. It is a hard task. Certainly, for CMOS technology it would be really difficult to imagine that we can force something like a small collection of transistors dynamically learn and optimize its functionality. But there are ways of going pretty close to that. One of them seems to be the direction of learning automata. Read about Tsetlin automata, for example (https://en.wikipedia.org/wiki/Tsetlin_machine) , in the recent work of Ole-Christoffer Granmo.