"It gives the limitation of parallel processing, and does not matter how much you have improved your hardware," Xian-He said. "Gustafson's law says there is no limitation of parallel processing if you allow problem size increase."
Xian-He revisited Amdahl's law and established Sun-Ni's law, which introduces memory constraint as a limitation on problem execution.
"With the long-standing memory-wall problem and the newly emerged big data problem, the problem size increase, however, is limited by memory access delay," Xian-He said, adding that memory-bound speedup needs to be followed.
"That means software models and hardware need to be redesigned to reduce data access time in order to get better scalability," Xian-He said.
While new theories will provide new insights, Amdahl's law provides a base.
"As with all real laws and theorems, one must always revisit things like the main assumptions, just as Gustafson did. The original law still stands, but corollaries might be very interesting," said University of Alberta's Lu.
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