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Fascinating paper. Thanks for the ref. Operating transistors outside the linear region (the saturated "on") on a billion+ scale is something that we as engine
by quanto 2y ago
Fascinating paper. Thanks for the ref.
Operating transistors outside the linear region (the saturated "on") on a billion+ scale is something that we as engineers and physicists haven't quite figured out, and I am hoping that this changes in future, especially with the advent of analog neuromorphic computing. The quadratic region (before the "on") is far more energy efficient and the non-linearity could actually help with computing, not unlike the activation function in an NN.
Of course, the modeling the nonlinear behavior is difficult. My prof would say for every coefficient in SPICE's transistor models, someone dedicated his entire PhD (and there are a lot of these coefficients!).
I haven't been in touch with the field since I moved up the stack (numerical analysis/ML) I would love to learn more if there has been recent progress in this field.
- ImHereToVote 2y agoI believe neuromorphic spiking hardware will be the step to truly revolutionize the field of anthropod contagion issues.
- trainsarebetter 2y agoCan’t tell if this is a joke or not
- burnished 2y agoI came in already knowing what neuromorphic hardware is and I'm also unsure
- fouc 2y agojoke I think, anthropod is probably another way of saying bugs/ants haha
- burnished 2y agoOh christ you're right, they were actually being really funny. I was being super literal and imagined them being very excited about futuristic advances in giant isopod diagnosis and care
- ImHereToVote 2y agoYeah, anthropic bugs. The planet is infested with them.
- deleted 2y ago[deleted]
- Sharlin 2y ago*arthropod, as in "joint(ed) leg" (cf. arthritis), GP misspelled it. "Anthropod" would mean something like "human leg".
- yencabulator 2y agoAI-created chips will be so weird, instead of bugs they'll have aliens: https://monster.fandom.com/wiki/Anthropod https://monster.fandom.com/wiki/Anthropod
- sat_solver 2y agoBug zapper
- igleria 2y agoat last, something possibly more buggy than vibe coding!
- gtirloni 2y agoMy thoughts, exactly.
- Aurornis 2y agoThe machine learning model didn’t discover something that humans didn’t know about. It abused some functions specific to the chip that could not be repeated in production or even on other chips or other configurations of the same chip. That is a common problem with fully free form machine learning solutions: They can stumble upon something that technically works in their training set, but any human who understood the full system would never actually use due to the other problems associated with it. > The quadratic region (before the "on") is far more energy efficient Take a look at the structure of something like CMOS and you’ll see why running transistors in anything other than “on” or “off” is definitely not energy efficient. In fact, the transitions are where the energy usage largely goes. We try to get through that transition period as rapidly as possible because minimal current flows when the transistors reach the on or off state. There are other logic arrangements, but I don’t understand what you’re getting at by suggesting circuits would be more efficient. Are you referring to the reduced gate charge?
- adrian_b 2y agoThe previous poster was probably thinking about very low power analog circuits or extremely slow digital circuits (like those used in wrist watches), where the on-state of the MOS transistors is in the subthreshold conduction region (while the off state is the same off state as in any other CMOS circuits, ensuring a static power consumption determined only by leakage). Such circuits are useful for something powered by a battery that must have a lifetime measured in years, but they cannot operate at high speeds.
- nextaccountic 2y agoIn other words, optimization algorithms in general are prone to overfitting. Fortunately there are techniques to deal with that. Thing is, once you find a solution that generalize better to different chips, it probably won't be as small as the solution found.
- Thorondor 2y ago> Take a look at the structure of something like CMOS and you’ll see why running transistors in anything other than “on” or “off” is definitely not energy efficient. In fact, the transitions are where the energy usage largely goes. We try to get through that transition period as rapidly as possible because minimal current flows when the transistors reach the on or off state. Sounds like you might be thinking of power electronic circuits rather than CMOS. In a CMOS logic circuit, current does not flow from Vdd to ground as long as either the p-type or the n-type transistor is fully switched off. The circuit under discussion was operated in subthreshold mode, in which one transistor in a complementary pair is partially switched on and the other is fully switched off. So it still only uses power during transitions, and the energy consumed in each transition is lower than in the normal mode because less voltage is switched at the transistor gate.
- nyeah 2y agoI'm having trouble understanding. Chips with very high transistor counts tend to use saturation/turn-off almost exclusively. Very little is done in the linear region because it burns a lot of power and it's less predictable.
- shermantanktop 2y ago> Operating transistors outside the linear region (the saturated "on") Do fuzz pedals count? To be fair, we know they work and basically how they work, but the sonic nuances can be very hard to predict from a schematic.
- nimish 2y ago>Operating transistors outside the linear region (the saturated "on") on a billion+ scale The whole point of switching transistors is that we _only_ operate them in the fully saturated on or totally off IV-curve region? Subthreshold circuits are commercially available, just unpopular since all the tools are designed for regular circuits. And the overlap between people who understand semiconductors and people who can make computational tools is very limited, or it's just cheaper to throw people+process shrinks at the problem.