5 ms·

It's trivial to beat a generic CPU by 1000x with a specialised ASIC or even an FPGA in many cases (think cryptography, for example).

by sklogic 11y ago

adwn 11y ago
Make that a few cases for FPGAs. Modern desktop CPUs are incredibly fast and run circles around modern FPGAs, even for many specialized, repetitive, parallel, integer-computation-bound algorithms. Of course, there are a couple of applications where FPGAs are actually faster than CPUs. Source: I'm an FPGA developer with a software engineering background.
- sklogic 11y ago
  > Modern desktop CPUs are incredibly fast and run circles around modern FPGAs Yep. At a tiny price of tenths of W of TDP. FPGAs shine in communication, not in computing. Fast isolated memories, wide channels (as wide as you like), etc. And there are far more tasks where you have to juggle gigabytes of data as fast as possible than the tasks where you have to maximise FLOPS.
- kragen 11y ago
  That's fascinating and startling! Why is that? Is it that the FPGA's cost per bit operation is just so many times larger than the CPU's that the FPGA can't compete? Where do GPUs fit in?
  - adwn 11y ago
    Several factors: 1) FPGAs are much slower due to the overhead of the flexibility they provide. With a lot of effort, you can get some FPGA designs (not even all of them!) to maybe 400 MHz on the more expensive FPGAs, and then it will do much less per cycle compared to an ASIC (CPUs are ASICs), so you need deep pipelines, with all the cost, complexity, and restrictions this entails. 2) CPUs have a lot of memory on-chip in the form of cache (several MiB), and they have sophisticated prefetch logic. In FPGAs, memory comes in several 100 blocks of, say, 4 kiB (depending on FPGA model). All memory management is purely manual. 3) CPUs tend to have a much higher external memory bandwidth. 4) Complex operations that are not directly provided by the FPGA fabric, like floating-point arithmetic or large memories with more than two ports, are expensive in terms of area and performance. 5) Modern desktop CPUs are incredibly well optimized: high clock frequency, out-of-order execution, superscalarity with several execution units, SIMD, automatic cache management, branch prediction, ... It's just very hard to beat that, and this is only possible for certain, very restricted applications. Highly parallel DSP (Digital Signal Processing) with integer/fixed-point arithmetic comes to mind.

It's trivial to beat a generic CPU by 1000x with a specialised ASIC or even an FPGA in many cases (think cryptography, for example).

by sklogic 11y ago

It's trivial to beat a generic CPU by 1000x with a specialised ASIC or even an FPGA in many cases (think cryptography, for example).

adwn 11y ago

Make that a few cases for FPGAs. Modern desktop CPUs are incredibly fast and run circles around modern FPGAs, even for many specialized, repetitive, parallel, integer-computation-bound algorithms. Of course, there are a couple of applications where FPGAs are actually faster than CPUs. Source: I'm an FPGA developer with a software engineering background.

sklogic 11y ago
> Modern desktop CPUs are incredibly fast and run circles around modern FPGAs Yep. At a tiny price of tenths of W of TDP. FPGAs shine in communication, not in computing. Fast isolated memories, wide channels (as wide as you like), etc. And there are far more tasks where you have to juggle gigabytes of data as fast as possible than the tasks where you have to maximise FLOPS.
kragen 11y ago
That's fascinating and startling! Why is that? Is it that the FPGA's cost per bit operation is just so many times larger than the CPU's that the FPGA can't compete? Where do GPUs fit in?
- adwn 11y ago
  Several factors: 1) FPGAs are much slower due to the overhead of the flexibility they provide. With a lot of effort, you can get some FPGA designs (not even all of them!) to maybe 400 MHz on the more expensive FPGAs, and then it will do much less per cycle compared to an ASIC (CPUs are ASICs), so you need deep pipelines, with all the cost, complexity, and restrictions this entails. 2) CPUs have a lot of memory on-chip in the form of cache (several MiB), and they have sophisticated prefetch logic. In FPGAs, memory comes in several 100 blocks of, say, 4 kiB (depending on FPGA model). All memory management is purely manual. 3) CPUs tend to have a much higher external memory bandwidth. 4) Complex operations that are not directly provided by the FPGA fabric, like floating-point arithmetic or large memories with more than two ports, are expensive in terms of area and performance. 5) Modern desktop CPUs are incredibly well optimized: high clock frequency, out-of-order execution, superscalarity with several execution units, SIMD, automatic cache management, branch prediction, ... It's just very hard to beat that, and this is only possible for certain, very restricted applications. Highly parallel DSP (Digital Signal Processing) with integer/fixed-point arithmetic comes to mind.