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>energy efficiency is the next key metric, and that specialized hardware (like TPU) might be the future. This is nonsense pushed forward by large corporations

>energy efficiency is the next key metric, and that specialized hardware (like TPU) might be the future. This is nonsense pushed forward by large corporations who want to own all your data and computational capacity.

johnfactorial 7y ago
Admittedly knowing little about how multi-core CPUs work, I've always thought the next breakthrough in CPU tech would be a hardware-based scheduler, a chip that effectively load balances threads to ensure all cores are used equally and simplifies the writing of software. The dev writes thread-safe code and the hardware does the rest. I wonder how feasible that really is.
- bwoj 7y ago
  This is essentially what hyper-threading in modern processors is attempting to do.
- Mvhsz 7y ago
  That sounds perfectly reasonable to me, but John Hennessy literally wrote the book on computer architecture. Towards the end of the deck he has a slide that we shouldn't expect large gains from improved architecture (on general purpose chips) in the future. I'm inclined to believe him, although I would be interested in hearing a deeper proof/disproof of the architecture you proposed.
sdenton4 7y ago
No, it's not? Point one: Indeed, untold millions of dollars can be saved by improving data center efficiency. But if the processors are in desktops instead, where the price pain isn't actually enough to drive improvements in efficiency, then we as a society just pay a higher power bill... Furthermore, data center power tends to be greener than general purpose city grids. Point two: they could have as easily said GPUs to avoid the fear of data centre only proprietary lock in... The point is the same: we seem to have hit the point where specialized linear algebra coprocessors make a huge difference.
- gambler 7y ago
  >price pain isn't actually enough to drive improvements in efficiency You have something reversed here. Hardware companies that make consumer devices are pumping barrels of money in improving CPU power usage to enable longer battery life on mobile devices. Google, on the other hand, promotes insanely power-hungry neural nets as the future of computing, because that's the kind of future that gives them the deciding edge in the market.
musicale 7y ago
Energy efficiency (performance/watt) is the key metric because servers are limited by cooling/power dissipation and mobile is limited by battery capacity. His chart shows TPU with ~80x the performance/watt of a CPU, indicating the potential advantages of domain-specific architectures over general purpose for specific applications. None of this should be surprising to anyone who uses a GPU.

johnfactorial 7y ago

Admittedly knowing little about how multi-core CPUs work, I've always thought the next breakthrough in CPU tech would be a hardware-based scheduler, a chip that effectively load balances threads to ensure all cores are used equally and simplifies the writing of software. The dev writes thread-safe code and the hardware does the rest. I wonder how feasible that really is.

bwoj 7y ago
This is essentially what hyper-threading in modern processors is attempting to do.
Mvhsz 7y ago
That sounds perfectly reasonable to me, but John Hennessy literally wrote the book on computer architecture. Towards the end of the deck he has a slide that we shouldn't expect large gains from improved architecture (on general purpose chips) in the future. I'm inclined to believe him, although I would be interested in hearing a deeper proof/disproof of the architecture you proposed.

sdenton4 7y ago

No, it's not? Point one: Indeed, untold millions of dollars can be saved by improving data center efficiency. But if the processors are in desktops instead, where the price pain isn't actually enough to drive improvements in efficiency, then we as a society just pay a higher power bill... Furthermore, data center power tends to be greener than general purpose city grids. Point two: they could have as easily said GPUs to avoid the fear of data centre only proprietary lock in... The point is the same: we seem to have hit the point where specialized linear algebra coprocessors make a huge difference.

gambler 7y ago
>price pain isn't actually enough to drive improvements in efficiency You have something reversed here. Hardware companies that make consumer devices are pumping barrels of money in improving CPU power usage to enable longer battery life on mobile devices. Google, on the other hand, promotes insanely power-hungry neural nets as the future of computing, because that's the kind of future that gives them the deciding edge in the market.

musicale 7y ago

Energy efficiency (performance/watt) is the key metric because servers are limited by cooling/power dissipation and mobile is limited by battery capacity. His chart shows TPU with ~80x the performance/watt of a CPU, indicating the potential advantages of domain-specific architectures over general purpose for specific applications. None of this should be surprising to anyone who uses a GPU.