Daniel Lemire's blog

, 6 min read

The rise of dark circuits

8 thoughts on “The rise of dark circuits”

  1. Aykut says:

    You might want to check Circuits of the Mind by Leslie G. Valiant (https://www.amazon.com/Circuits-Mind-Leslie-G-Valiant/dp/019508926X). It asks more questions than providing answers but still good read.

  2. Chris Nahr says:

    Small correction: “memory usage due to memory” should be “energy usage due to memory.”

    Regarding avoiding the use of most memory most of the time, we have already a precedent for that: the slow storage hierarchy of tape, disk & RAM that dominated classic textbooks. Merge Sort will return with a vengeance!

  3. Max Lybbert says:

    I first ran across the term “dark silicon” in Herb Sutter’s “Welcome to the Jungle” ( https://herbsutter.com/welcome-to-the-jungle/ ). That vision also freaked me out, not because we won’t keep things powered all the time, but because it’s easiest to turn things on/off in groups, and as a programmer I have a hunch I’ll be responsible for managing those groups (it was also the first place I learned that GPUs have wildly different architecture than CPUs; guess who’s responsible for keeping the differences straight).

  4. trylks says:

    Referential proximity, functional programming and lazy evaluation.

    Maybe it would have been wiser to focus on the lambda calculus instead of the Turing machine.

    But such a future is still far from certain.

  5. Blue Whale says:

    Man has evolved to be different than most other species. We endeavor to be better by building smarter and faster machines and genetic engineering. And now the newer machines will be built mimicking biological architecture and processes 🙂

    Definitely thought provoking.
    I wonder if we could come up with a definition of a “gene” for these biologically patterned machines and then let such machines evolve. Looks like we’ll have to come up with an “evolution algorithm” as well.

  6. Richard says:

    I’ve often wondered why we don’t put more of libc into silicon.
    For example, printf() is remarkably slow; a dedicated hardware implementation might take up tens of thousands of gates, but transistors are cheap, and it could be much faster and less power-hungry.

    1. Paolo G. Giarrusso says:

      Aren’t SSE extensions, hardware cryptography and FPGA about doing exactly that? I guess printf is just not the perfect example (its spec. is not fixed enough, and were it ever performance critical, we can optimize it in software by compiling format strings).

      1. Aren’t SSE extensions, hardware cryptography and FPGA about doing exactly that?

        Yes.