I worked on hardware for something akin to a FPGA on a much coarser granularity (kind of like coarse-grained reconfigurable arrays)--close enough that you have to adapt tools like place-and-route to compile to the hardware. The programming for this was mostly driven in pretty vanilla C++, with some extra intrinsics thrown in. This C++ was close enough to handcoded performance that many people didn't even bother trying to tune their applications by resorting to hand-coding in the assembly-ish syntax.
This helped bolster my opinion that FPGAs aren't really the answer that most people are looking for, and that there are useful nearby technologies that can leverage the benefits of FPGAs while having programming models that are on par with (say) GPGPU.
For sure. FPGAs are probably not the answer that most people are looking for. FPGAs are but one point in the trade-off space, and they're not one you jump to "just because".
> [...] there are useful nearby technologies that can leverage the benefits of FPGAs while having programming models that are on par with (say) GPGPU
I think CGRAs are really cool but they're even more niche, and I suspect your original point about GPUs eating everyone's lunch applies particularly strongly to CGRAs. The point is well taken, though, and I don't necessarily disagree.
I worked on hardware for something akin to a FPGA on a much coarser granularity (kind of like coarse-grained reconfigurable arrays)--close enough that you have to adapt tools like place-and-route to compile to the hardware. The programming for this was mostly driven in pretty vanilla C++, with some extra intrinsics thrown in. This C++ was close enough to handcoded performance that many people didn't even bother trying to tune their applications by resorting to hand-coding in the assembly-ish syntax.
This helped bolster my opinion that FPGAs aren't really the answer that most people are looking for, and that there are useful nearby technologies that can leverage the benefits of FPGAs while having programming models that are on par with (say) GPGPU.