|
|
|
|
|
|
by aeonfox
60 days ago
|
|
|
A) Wasn't the article suggesting that would be 4-bits end-to-end in this hypothetical photonic matrix multiplication co-processor? ie. the weights are 4-bits B) Power consumption and speed. Essentially chips are limited by the high resistance (hence heat loss) of the semiconductor. Photonics can encode multidimensionally, and data processing is as fast as the input light signal can be modulated and the output light signal can be interpreted. I guess this would favour heavy computations that require small inputs and outputs, because eventually you're bottlenecked by conventional chips. |
|
|
The intrinsic size of the optical computing elements is much larger, being limited by wavelength. Then a lot of additional devices are needed, for conversion between electrical and optical signals and for thermal management.
Optical computing elements can be advantageous only in the applications where electronic devices need many metallic interconnections that occupy a lot of space, while in the optical devices all those signals can pass through a layer of free space, without interfering with each other when they cross.
This kind of structure may appear when doing tensor multiplication, so there are indeed chances that optical computing could be used for AI inference.
Nevertheless, optical computing is unlikely to ever be competitive in implementing general-purpose computers. Optical computers may appear but they will be restricted to some niche applications. AI inference might be the only one that has become widespread enough to motivate R&D efforts in this direction.