Analogue computing - why, how and where are we now?

Why analogue computing?

Digital computers, based on binary logic, have turned the world upside down within a lifetime. Processing power, data retention and connectivity have made so many contributions – positive and negative – to our lives that it isn’t worth even trying to summarise them. But all this comes at a high cost, in resources and energy. And it has limits, which will prevent many of the more outrageous claims about computing ever coming close to reality.

Analogue computers provide – or will provide – solutions to these problems. Here we look more closely at the issues with digital, and how analogue addresses them, with reference to the highly practical descriptions of the software that defines the proposed analogue architecture and its philosophical implications.

There was once a popular TV series which featured a game where contestants had to answer questions without using the words “yes” or “no”. It was tricky, as the host fired off a quick succession of questions that most naturally invited such a response. But imagine how much more difficult it would be to conduct a conversation in which only “yes” or “no” answer can be given. For example, to find out how many people there are in a respondent’s family, the logical way would be to ask questions that narrow the options in a number of steps, for example, if the answer were 5, the questions might go: is it 8 or more? No. Is it 4 or more? Yes. Is it 6 or more? No. Is it 5? Yes.

It gets to the answer, but it is very clumsy. But this is how a digital computer works – everything a computer processes, it handles as a sequence of binary values: yes/no, true/false, 0/1. The sequence of questions in the example shows how a numerical value is coded in a computer – the sequence No, Yes, No, Yes becomes 0101 – the binary representation of the number 5. This digital clumsiness is generally hidden from users, who see how smoothly and easily their PCs and phones handle any type of information or data. But this illusion comes at a great cost. It involves billions of electronic transistors working at a tremendous rate and consuming large amounts of power, heating up our devices and putting a massive strain on electrical power supplies for data centres.

The above explains two of the ways that analogue computing could use less resources than digital. Firstly, by needing less energy to perform smooth transitions than what is needed to drive binary jumps, and secondly by using fewer units to encode values (one analogue value requires many digital bits to represent the same information).

This benefit conceals a more subtle one in terms of performance. Chez digital, where a single value requires multiple gates to represent it, it is necessary to ensure that the gates are perfectly synchronised. (In fact, they cycle through transition phases, when their outputs are changing and cannot reliably be read, and clocked phases when they are all stable and their outputs are valid.) From this arises the need for a central master clock and also the basic clunkiness of a digital computer – it is moved from one static state to the next, in rhythm with the clock. In fact, this is what allows a computer to be stopped, its status recorded and frozen in time until it is restarted as if nothing had happened. (Which also gives rise to the popular, but nonsensical, SF trope of copying or preserving brains.)

Analogue computers are asynchronous. Because their basic components are cells behaving autonomously, they are free to vary continuously and smoothly, with no need for a central clock. And the fact they behave autonomously provides another major advantage over digital – there is no central processor forming a major bottleneck and limiting the growth possibilities of the system – cells can be added to form massive parallel systems with no additional overhead

Analogue computers are configured, not programmed. Having no central processor means no central process, or program. It means no distinction between “program code” and “data”. It means adaptation, habituation and learning can be configured at the qcell level, leading to systems that are inherently flexible and responsive to their environments.

What is the analogue computer that QQRONA proposes?

To understand better the nature of what is proposed, it helps first to look into the heart of a digital computer. Here the binary logic is implemented by a large array of logic “gates”, which consist of electronic transistors and come in a limited number of varieties. These perform the logic functions originally devised by mathematicians such as Frege and Boole. Considering gates that have two inputs:

• AND gates output 1 only if both inputs are 1

• OR gates are 1 if one or two inputs are 1

• XOR (exclusive OR) if only one input is 1

Negative versions of the gates (eg NAND, NOR) invert the output value.All computer and other digital devices are built up from these few basic gates.

Other features of these gates are that:

• they require energy. Transistors are “active” components that need a power source to force them into the 1 or 0 output state

• their outputs are only considered valid when they have settled into their final state, which may take a little time. These means that the whole array of gates has to be sampled at fixed intervals, with all transitions taking place simultaneously in between samples

• gates are entirely reactive; their outputs change only as a direct response to their inputs

• any gate may take as inputs the data which they process, and the program code which represents the instructions from their operating system telling them how to process it

The name “gate” is quite appropriate – one can imagine a long row of gates, with people lined up on either side, waiting. Every now and then, all the gates open simultaneously, at which point some people pass through, according to how they have been instructed. The gates are then closed again, until the next opening. Of course, in modern digital devices, the gates are opening and closing billions of times per second.

QQRONA uses a small variety of standard components to build up complex systems in a similar way to logic gates, to build up into complex functional systems. However, these components, called QQRONA cells or qcells are quite different from digital gates:

• their outputs may vary constantly

• between 0 and 1

• qcells are configured how to respond to their inputs not by defining their output value, but the rate at which the output varies in response to the input

• qcells are asynchronous and autonomous – they act independently and need no central program or processor to drive them

• the gradual changes in output occur naturally, rather than being forced to extremes, requiring less energy

These characteristics at the basic qcell level give rise to the behavioural characteristics of QQRONA as a whole:

• lower energy requirement

• dynamic behaviour

• no distinction between data and program code

• outputs convey much more information hence are more efficient

What applications best suit analogue?

QQRONA’s unique strength lies in modelling complex behavioural systems characterised by multiple feedback circuits, such as animal nervous systems and weather systems, where traditional mathematics techniques become cumbersome and require massive digital processing power.

However, QQRONA is suitable for any application processing real world, analogue information, for example scientific, modelling, medical and real time control. Note that QQRONA is designed around an efficient, low resource core model which can be taken out of the toolkit development environment and deployed in an embedded control system.

Where are we now with analogue computing?

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