Thermodynamic Computing - A New Computer Architecture

All matter and energy in the universe obeys the laws of thermodynamics, which dictate how energy and heat behave in any system. These principles have inspired a new approach to computing called Thermodynamic Computing, where the natural fluctuations and noise of energy are harnessed to perform computations more efficiently.

Thermodynamic Computing has the potential of dramatically improving our ability to leverage the most advanced AI models, while reducing energy consumption by orders of magnitude. 

Today’s computer architecture is digital. Whether it is a computer in your pocket or on your desktop or a server in the cloud, you are using a transistor based system. If you use a Computer Processor Unit (CPU), a Graphical Processing Unit (GPU) or a Text Processing Unit (TPU), you are using a device made up of digital switches and digital memory. 

New quantum-based architectures are also being developed which leverage the ability to engineer systems that operate on quantum mechanical. These go beyond simple digital systems since they can exploit quantum effects like superposition, entanglement, and quantum tunnelling. 

Thermodynamic Computing is a third approach. It is not based on transistors or qubits. It is based on the ability to capture and use energy from the continuous motion and of all matter.

At a molecular level, all matter is always in motion. Even when cooled to the theoretical limits of cold, matter still vibrates. Warmer matter vibrates more. With vibrations of charged particles come disruptions of the electromagnetic field and noise that spreads beyond just collisions of molecules. Designers of digital computers and researchers building quantum systems fight this reality of continuous noise every day. Architects building new thermodynamic computing approaches embrace the noise. 

The thermodynamic reality of matter and its inherent noise is like a noisy ocean full of waves and constant movement.  This reality of the physical world can be used the way a surfer harnesses the noisy waves of the sea. A surfer does not fight the wave, a surfer uses the wave.

The goal of Thermodynamic Computing is to smartly channel the constant noise of matter into useful computing power. Rather than resisting these forces, as traditional digital and quantum systems often do, this new architecture embraces them, turning a natural source of randomness into an asset. In doing so, it promises a more energy-efficient future for AI and neural network models. Its exponents say that Thermodynamic Computing has the potential to transform our approach to computational power, reducing the barriers imposed by energy limitations and paving the way for advancements that align more closely with the fundamental laws of the universe.

The US National Science Foundation (NSF) estimates that computers use between 5% and 9% of global generated power, but at current growth rates, that could reach 20% by 2030.  But previous work by researchers suggests modern computers are grossly inefficient: Biological systems, by contrast, are about 100,000 times more energy-efficient than human-built computers. 

The primary motivations for a general thermodynamic theory of computation is to find new ways to reduce the energy consumption of real-world machines. 

Thermodynamic computing is particularly well-suited for searching complex energy landscapes that leverage both rapid device fluctuations and the ability to search a large space in parallel, addressing  combinatorial optimisation problems and sampling many-variable probability distributions.

NSF   |   HPCWire   |   Science Daily   |   Oodlaloop   |   Rafał Wiatrowski / LinkedIn  |  Wikipedia

Image: Viktor Forgacs

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