4 ms·

http://en.wikipedia.org/wiki/Parallel_computing#Amdahl.27s_law_and_Gustafson.27s_law http://en.wikipedia.org/wiki/Parallel_computing#Amdahl.27s_l... Basically,

http://en.wikipedia.org/wiki/Parallel_computing#Amdahl.27s_law_and_Gustafson.27s_law http://en.wikipedia.org/wiki/Parallel_computing#Amdahl.27s_l... Basically, you will never get a linear increase with parallel computing, especially on consumer type apps that are much more synchronous. So running multiple cores, with requisite context switches will get less computing per watt, even if it isn't as bad as the 2x number.

sparky 17y ago
"with requisite context switches" Can you explain this part?
- cschneid 17y ago
  A generic catchall for OS level crap that multi-core requires. Interrupts / memory management / ... other stuff.... I'm only really aware that there's overhead, and not the specifics of what it ends up being.
chadaustin 17y ago
Sort of. Herb Sutter shows some examples where executing programs in parallel gives superlinear speed-ups: http://herbsutter.wordpress.com/2008/01/30/effective-concurrency-going-superlinear/ http://herbsutter.wordpress.com/2008/01/30/effective-concurr...
- anamax 17y ago
  > Herb Sutter shows some examples where executing programs in parallel gives superlinear speed-ups His definition of "superlinear" is a bit tricky. As he explains, you can only get superlinear by "Do disproportionately less work." and/or "Harness disproportionately more resources.". However, his example of the former is actually a subtle instance of the latter. Superlinear speedups are always due to more effective caching. Sutter uses "disproportionatly more resources" when the added effectiveness comes from larger caches. However, his "do less work" examples are "just" better cache behavior.