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NL-Complexity appears to be related to NP-complexity, and i would like a non-mathematic explanation (being that i only have a passing familiarity with the level of mathematics used in that article). Can someone provide a description of how it relates to programming and NP-complexity?
Algorithms that have NL-Complexity can run in a memory space that grows only logarithmically (very slowly) with the size of the problem. Inotherwords, these problems would scale up very well in relation to the required memory usage – double the problem size and you’d hardly need anymore memory to run the algorithm to completion. I don’t know if there is a theoretical relationship proven between NL and NP complexity sets. NP complexity relates to the time that it takes to complete a program – whereas NL complexity is characterizing the memory space needed to complete a program.
I did notice in that wiki article that you referred to that it is not known if NL=P. This seems unlikely as it would mean that all algorithms that can complete in polynomial time (w.r.t their size) can also finish in a memory space that scales logrithmically w.r.t. problem size. If only that were true! For now we only know that NL is contained in P.
-Paul