Temporal Computing In Detail
The key new idea in temporal computing is that input data is represented as a passage of time. Typically this may be the time taken for some noticeable change to happen in either an analog or digital signal. This gives an underlying representational scheme based not on traditional binary, but on unary and unary coding schemes expressed as time.
Unary number systems were among st the earliest numerical representation of quantity, with the abacus existing as the earliest calculating device and this simplicity offers significant processing efficiencies and is thought to be central to the brain’s ability to data process. This allows us to perform much of the processing using simpler memory manipulation devices that can function closer to memory storage, giving a saving in the “space” required to build the processor, and the energy used to move data between memory and the processor.
The Potential
Our technology caters to cloud data centres, mobile devices, desktop processors, and IOT embedded devices, with a focus on Deep Learning and high-performance systems.
Our unique approach, not limited by traditional binary systems and targeted at AI/DL architectures, allows us to compete in the neuromorphic market and offer general technology for a wider range of opportunities. We plan to demonstrate supremacy in a valuable area and explore commercial exploitation opportunities, focusing on autonomous/driverless car embedded systems due to their use of temporally encoded data sources.
We aim to develop a licensable portfolio, unlock future investment, and accelerate customer engagement, following the successful models of Arm and Imagination.
Comparisons with Quantum Computing
Some of theadvantages over Quantum Computing are:
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Easier development phase - as we will see there are huge advantages to temporal in terms of ease of implementation. This even extends to use of existing fabrication methods and hence may actually prolong the use of silicon as a compute medium.
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Extension into very fast sequential compute - anything that oscillates can be used to compute - there is significant “room” at the bottom when it comes to the physical manifestation of temporal computers
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High parallelisation capacity - time is a free resource so essentially it cost nothing to use it as memory, also it is easily parallelised it is trivial to measure two events next to each other without any need to coordinate. Quantum memory is still a very open area of research.
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Low resource - it is almost certain that initial quantum computers will be offered as a centralised service, temporal in contrast because of its potential simple implementations and design, can easily be thought of as working in smaller systems in edge and mobile devices
The Patent
We have patented technology surrounding the operation of a Multiply Accumulate (MAC) unit, this work was presented at the ASYNC19 conference.