That article is really low on details and mixes up a lot of things. It compares microleds to traditional WDM fiber transmission systems with edge emitting DFB lasers and ECLs, but in datacentre interconnects there's plenty of optical links already and they use VCSELs (vertical cavity surface emitting lasers), which are much cheaper to manufacture. People also have been putting these into arrays and coupling to multi-…
I guess they are doing direct modulated IMDD for each link so the DSP burden is not related to the coherence of diodes? Also indeed very short reach in the article.
That article is really low on details and mixes up a lot of things. It compares microleds to traditional WDM fiber transmission systems with edge emitting DFB lasers and ECLs, but in datacentre interconnects there's plenty of optical links already and they use VCSELs (vertical cavity surface emitting lasers), which are much cheaper to manufacture. People also have been putting these into arrays and coupling to multi-…
short links it’s in the article
Ah I missed the 10m reference there. I'm not sure it makes more sense though. Typical intra-datacenter connections are 10s-100s of meters and use VCSELs, so introducing microleds just for the very short links instead of just parallelising the VCSEL connections (which is being done already)? If they could actually replace the VCSEL I would sort of see the point.
There is also optical neuromorphic computing, as an alternative to electronic neuromorphic computing like memristors. It's an fascinating field, where you use optical signals to perform analog computing. For example: https://www.nature.com/articles/s41566-020-00754-y https://www.nature.com/articles/s44172-022-00024-5 As far as I understood, you can only compute quite small neural networks until the noise signal gets…
The issue with optical neuromorphic computing is that the field has been doing the easy part, i.e. the matrix multiplication. We have known for decades that imaging/interference networks can do matrix operations in a massively parallel fashion. The problem is the nonlinear activation function between your layers. People have largely been ignoring this, or just converted back to electrical (now you are limited again by the cost/bandwidth of the electronics).
That article is really low on details and mixes up a lot of things. It compares microleds to traditional WDM fiber transmission systems with edge emitting DFB lasers and ECLs, but in datacentre interconnects there's plenty of optical links already and they use VCSELs (vertical cavity surface emitting lasers), which are much cheaper to manufacture. People also have been putting these into arrays and coupling to multi-…
I guess they are doing direct modulated IMDD for each link so the DSP burden is not related to the coherence of diodes? Also indeed very short reach in the article.
The problem with both leds and imaging fibres is that modal dispersion is massive and completely destroys your signal after only a few meters of propagation. So unless you do MMSE (which I assume would be cost prohibitive), you really can only go a few meters. IMDD doesn't really make a difference here.
There is also optical neuromorphic computing, as an alternative to electronic neuromorphic computing like memristors. It's an fascinating field, where you use optical signals to perform analog computing. For example: https://www.nature.com/articles/s41566-020-00754-y https://www.nature.com/articles/s44172-022-00024-5 As far as I understood, you can only compute quite small neural networks until the noise signal gets…
The issue with optical neuromorphic computing is that the field has been doing the easy part, i.e. the matrix multiplication. We have known for decades that imaging/interference networks can do matrix operations in a massively parallel fashion. The problem is the nonlinear activation function between your layers. People have largely been ignoring this, or just converted back to electrical (now you are limited again b…
Seems hard to imagine there’s not some non-linear optical property they could take advantage of
The issue with optical neuromorphic computing is that the field has been doing the easy part, i.e. the matrix multiplication. We have known for decades that imaging/interference networks can do matrix operations in a massively parallel fashion. The problem is the nonlinear activation function between your layers. People have largely been ignoring this, or just converted back to electrical (now you are limited again b…
Seems hard to imagine there’s not some non-linear optical property they could take advantage of
The problem is intensity/power, as discussed previously photon-photon interactions are weak, so you need very high intensities to get a reasonable nonlinear response. The issue is, that optical matrix operations work by spreading out the light over many parallel paths, i.e. reducing the intensity in each path. There might be some clever ways to overcome this, but so far everyone has avoided that problem. They said we did "optical deep learning" what they really did was an optical matrix multiplication, but saying that would not have resulted in a Nature publication.
Optics also have signal integrity issues. In practice OSNR and SNR limit optics. Cutting the fiber still breaks it. Small vibrations also affect the signal's phase.
Phase variations will not introduce any issues here, they most certainly are talking about intensity modulation. You can't really (easily) do coherent modulation using incoherent light sources like leds. SNR is obviously an issue for any communication system, however fiber attenuation is orders of magnitude lower than coax. The bigger issues in this case would be mode-dispersion, considering that they are going throu…
Mode dispersion is frequency dependent phase changes.
As I understand it (from designing high-speed electronics), the major limitations to data/clock rates in copper are signal integrity issues. Unwanted electromagnetic interactions all degrade your signal. Optics is definitely a way around this, but I wonder if/when it will ever hit similar limits.
We already regularly run into optical nonlinearity issues in submarine cables. The instantaneous EM fields generated in high bandwidth fiber are sufficiently strong to cause nonlinear interactions with the fiber medium that we have to correct for.
This comment appears insightful but I have no idea what it means. Can someone elaborate?
Electrons are fermions which means that two electrons can't occupy the same quantum state (Pauli exclusion principle). Bosons don't have the limit so I believe that implies that you can have stronger signals at the low end since you can have multiple photons conveying or storing the same information.