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FPGAs with larger cells (e.g., entire ALUs) can potentially beat all the shit out of GPUs in most use cases (because of the better control over memories). You'l

by sklogic 11y ago

FPGAs with larger cells (e.g., entire ALUs) can potentially beat all the shit out of GPUs in most use cases (because of the better control over memories). You'll have the best of both worlds here - routing flexibility of FPGAs and fast ASIC cells.

dogma1138 11y ago
That's not really true FPGA CPU's tend to be very slow relatively to the speed of the FPGA and comparable ASIC's. Yes you can program the FPGA to do say LZMA very quickly but you can just as well build a dedicated SIMD ASIC that will do the same and at much lower cost. If you design your CPU to include current ISA big cores combined with small mission specific SIMD ASIC's it will be better than building a CPU with additional FPGA cores or building a CPU on an FPGA which is an insanity to begin with. I would yield that FPGA are more flexible but if you can build more or less flexible SIMD ASIC's that are user configurable you will get a similar flexibility to FPGA's with better performance still, eventually there's a limit to how many non-generic operations the CPU handles and there will be a fairly low limit on how many of those will deserve dedicated silicon before you over-optimize and lose performance.
- sklogic 11y ago
  I am talking of really large but generic cells, much bigger then the current DSP slices. This way FPGA will be a programmable dataflow machine with all the heavy lifting done by the ASIC ALU slices. And it is much more flexible than hoarding the very specific ASIC blocks. Any problem I was solving on GPUs recently would have been implemented 100x times more efficiently on such an architecture.
  - dogma1138 11y ago
    large and generic cells seem to be exactly what the current GPU architectures bring, and where did the 100x times number came from?
    - sklogic 11y ago
      The current GPUs have to deal with a cumbersome, often unfit memory hierarchy. What an FPGA-like model would bring is a much more flexible way to configure the local memories layout. Source - experience of getting over 100x difference in performance wity memory opimisations alone.

by sklogic 11y ago

dogma1138 11y ago

That's not really true FPGA CPU's tend to be very slow relatively to the speed of the FPGA and comparable ASIC's. Yes you can program the FPGA to do say LZMA very quickly but you can just as well build a dedicated SIMD ASIC that will do the same and at much lower cost. If you design your CPU to include current ISA big cores combined with small mission specific SIMD ASIC's it will be better than building a CPU with additional FPGA cores or building a CPU on an FPGA which is an insanity to begin with. I would yield that FPGA are more flexible but if you can build more or less flexible SIMD ASIC's that are user configurable you will get a similar flexibility to FPGA's with better performance still, eventually there's a limit to how many non-generic operations the CPU handles and there will be a fairly low limit on how many of those will deserve dedicated silicon before you over-optimize and lose performance.

sklogic 11y ago
I am talking of really large but generic cells, much bigger then the current DSP slices. This way FPGA will be a programmable dataflow machine with all the heavy lifting done by the ASIC ALU slices. And it is much more flexible than hoarding the very specific ASIC blocks. Any problem I was solving on GPUs recently would have been implemented 100x times more efficiently on such an architecture.
- dogma1138 11y ago
  large and generic cells seem to be exactly what the current GPU architectures bring, and where did the 100x times number came from?
  - sklogic 11y ago
    The current GPUs have to deal with a cumbersome, often unfit memory hierarchy. What an FPGA-like model would bring is a much more flexible way to configure the local memories layout. Source - experience of getting over 100x difference in performance wity memory opimisations alone.