2 docs tagged with "amdahl"

Buying a bigger GPU, or more of them, does not buy a proportionally bigger speedup, and the reason has nothing to do with the hardware being slow. It has to do with the fraction of the program that was never made parallel in the first place. Two laws describe the two ways to think about that fraction — one holds the problem size fixed and asks how fast you can finish it, the other holds the time budget fixed and asks how much bigger a problem you can solve — and knowing which one describes your situation changes what "more parallelism" is even supposed to buy you.

Most failed GPU ports do not fail because the kernel was slow. They fail because the workload was never shaped like something a GPU accelerates, and the port made that visible only after weeks of work. The kernel itself often does run twenty times faster than the CPU loop it replaced — and the program gets slower anyway, because the time now goes into transfers, synchronization, and the 60% of the runtime that was never offloaded at all.