2 ms·
They aren't inferior but you can't just multiply by 4 here either. You could turn a int32 adder into 4 int8 addres if the larger adder works on a ripple-carry
by Symmetry 9y ago
They aren't inferior but you can't just multiply by 4 here either. You could turn a int32 adder into 4 int8 addres if the larger adder works on a ripple-carry principle but really everybody uses ripple-carry or carry-bypass. And a float32 is more complex and you could get 3 int8s out of it but you'd have lots of transistors left over in the execution logic. But simple quantity of execution logic is almost never an interesting constraint in a design.
But the actually important part here is that the register and bypass networks to pass 4 bits of int8 data around are way more complicated than those required to pass a single float32 around and that's where Google's decision to restrict the flexibility of its TPU pays big dividends. NVidia's GPUs do not have broken designs. They're just making compromises based on the need to handle a wider variety of use cases.
- Dylan16807 9y ago> They aren't inferior but you can't just multiply by 4 here either. Yeah but there wasn't a suggestion to do so. Just by raw count there are issues with 25x. > NVidia's GPUs do not have broken designs. The part where the current generation sticks in a single FP16x2 unit per 128 FP32 units, so that if your code triggers them it runs 64x slower on FP16 while leaving all the FP32 units idle? That's broken as far as I can see, there to upsell you the pro cards. Anything that would make 8 bit math slower than 32 bit math is just a fundamental lack of forethought. It's not preferred by GPU design, and shouldn't be used as a point against GPUs in general.