Does Amdahl’s law really help?

Thu, 01/19/2012 - 7:29am
Juergen Mathes, Texas Instruments

Juergen Mathes-TIOne of the first topics you stumble over when discussing multicore and performance is Amdahl's law. This law is often used in parallel computing to calculate the theoretical maximum multicore performance. For example, if your code is serial to 50% and can be executed in parallel for the other half, the maximum speedup - versus a single core implementation - would be two times faster no matter how many cores you’d be using.

Multicore Board ShotPersonally, I believe it's good to be reminded that throwing more parallel computing power at the problem to speed up your code doesn't always help more - and the result that Amdahl’s formula is providing is too simplistic. Even though Amdahl's law is theoretically correct, the serial quota is not really practically obtainable. A simple example would be speculative execution of serial code that therefore could run in parallel. If the results of that speculative execution can be used, it should be considered parallel if not it should be considered serial. Also, Amdahl's law does not take into account the load balancing issues or the synchronization overhead. Sometimes you might also need a temporary performance lift to address quick response times and then fall back to a lower performance and lower power consumption mode by putting cores not needed into a sleep mode.

Now there are other laws, such as Gustafson’s law, that try to discuss tackling the parallel computing power. But is the speedup really all we care about when we turn to multicore? Maybe not. A device should unleash the full multicore computing power while consuming a limited amount of electrical power.

What more do you expect to get out of a multicore device? Comments are welcome.

I hope you enjoyed this read and stay tuned for more.

Kind regards,
one and zero

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