Are mult-adds and FLOPs equivalent? I am comparing different CNN architectures for edge implementation. Some papers describing architectures refer to mult-adds, like the MobileNet V1 paper, where it is claimed that this net has 569M mult-adds, and others refer to floating-point operations (FLOPs), like the CondenseNet paper claims 274M FLOPs.
Are these comparable? Is 1 multiply-add equivalent to 2 floating-point operations? Any direction will be greatly appreciated.
According to this source, one FLOP is roughly equal to two MAC (multiply accumulate). My guess/understanding would be that the distinction is made because neural nets spend compute overwhelmingly on multiply-accumulate operations, and thus optimizations and statistics over MAC operations would be more significant than FLOPs.