4 ms·

So time to write efficient code and start working hard on easy multi-threading? Cause if we hit "the wall", all consumers can do is buy the fastest CPU with the

So time to write efficient code and start working hard on easy multi-threading? Cause if we hit "the wall", all consumers can do is buy the fastest CPU with the most cores they can get, and then never in his live again will he be able to upgrade. So those resources is what we will need to do it with.

Qwertious 10y ago
I think when we actually hit The Wall, we'll keep on improving (at a slowed pace) for a while afterwards based on the not-so-low-hanging fruit we've ignored up til then.
- cbd1984 10y ago
  Frankly, I'm kind of interested in the prospect of specialized hardware coming back. The trend since the mid-1980s, when the Intel 80386 was introduced, has been for specialized chips to be replaced due to commodity chips beating them comprehensively in single-core speed; problems which once required specialized hardware and core designs were either solved or obviated by massive improvements in scalar hardware. Now that this brute force method is starting to peter out, we might see a rise of new, specialized designs once again, to solve specific problems which gain substantial speedups from very specific kinds of parallelism. Systolic arrays are one example. We're already doing something like this by pressing GPUs into service as computational hardware, but it can go farther.
  - Inthenameofmine 10y ago
    This is definitely already starting to happen. Modern server CPUs have FPGAs in them. I was able to speed up Blockchain transaction signing and verification by 2 order of magnitude by utilizing the Intel in-build FPGAs. Mobile phone SoCs already have semi-specialized processors in them. Microsoft's Hololens has something what they call "HPU" Holographic Processing Unit. Google just made public that they have a TensorFlow ASIC. Google's phone radar thingy has it's own ASIC if I'm not mistaken.

4 ms·

So time to write efficient code and start working hard on easy multi-threading? Cause if we hit "the wall", all consumers can do is buy the fastest CPU with the

by Qantourisc 10y ago

Qwertious 10y ago
I think when we actually hit The Wall, we'll keep on improving (at a slowed pace) for a while afterwards based on the not-so-low-hanging fruit we've ignored up til then.
- cbd1984 10y ago
  Frankly, I'm kind of interested in the prospect of specialized hardware coming back. The trend since the mid-1980s, when the Intel 80386 was introduced, has been for specialized chips to be replaced due to commodity chips beating them comprehensively in single-core speed; problems which once required specialized hardware and core designs were either solved or obviated by massive improvements in scalar hardware. Now that this brute force method is starting to peter out, we might see a rise of new, specialized designs once again, to solve specific problems which gain substantial speedups from very specific kinds of parallelism. Systolic arrays are one example. We're already doing something like this by pressing GPUs into service as computational hardware, but it can go farther.
  - Inthenameofmine 10y ago
    This is definitely already starting to happen. Modern server CPUs have FPGAs in them. I was able to speed up Blockchain transaction signing and verification by 2 order of magnitude by utilizing the Intel in-build FPGAs. Mobile phone SoCs already have semi-specialized processors in them. Microsoft's Hololens has something what they call "HPU" Holographic Processing Unit. Google just made public that they have a TensorFlow ASIC. Google's phone radar thingy has it's own ASIC if I'm not mistaken.