Think of FPGAs as having the potential to be primitive GPGPUs. They outperform CPUs in all the same areas GPUs outperform CPUs.
FPGAs are like GPUs with no floating-point, no caches, and limited local memory. But if you can implement a kernel in FPGA with comparable memory bandwidth, you'll usually outperform GPGPU while using as little as 1/50 the power.
> Think of FPGAs as having the potential to be primitive GPGPUs. They outperform CPUs in all the same areas GPUs outperform CPUs.
FPGAs have several orders of magnitude lower latency than GPGPU. GPUs have memory access latency of 1 microsecond, getting something useful out of them >1 ms. FPGAs can have state machines running at 200 MHz, or 5 ns cycle time.
> FPGAs are like GPUs with no floating-point, no caches, and limited local memory. But if you can implement a kernel in FPGA with comparable memory bandwidth, you'll usually outperform GPGPU while using as little as 1/50 the power.
Some FPGAs do have floating point hard blocks. Integrated SRAMs (syncram) can be used as caches and usually are. FPGAs usually have DRAM controllers as hard blocks, so local memory is not that limited. Unless you consider up to 8 GB (newer models up to 32 GB) limited.
FPGAs are like GPUs with no floating-point, no caches, and limited local memory. But if you can implement a kernel in FPGA with comparable memory bandwidth, you'll usually outperform GPGPU while using as little as 1/50 the power.