TL;DR: WJe show that every nondeterministic computational task S(Z, y), defined as a polynomial time relation between the instance x, representing the input and output combined, and the witness y can be modified to a task S such that each instance/witness pair becomes checkable in poly!ogariihmic Monte Carlo time.
Abstract: Motivated by Manuel Blum’s concept of inst ante checking, we consider new, very fast and generic mechanisms of checking computations. Our results exploit recent advances in interactive proof protocols [LFKN], [Sh], and especially the MIP = NEXP protocol from [BFL]. WJe show that every nondeterministic computational task S(Z, y), defined as a polynomial time relation between the instance x, representing the input and output combined, and the witness y can be modified to a task S such that: (i) the same instances remain accepted; (ii) each instance/witness pair becomes checkable in poly!ogariihmic Monte Carlo time; and (iii) a witness satisfying S’ can be computed in polynomial time from a witness satisfying S. Here the instance and the description of S have to be provided in error-correcting code (since the checker will not notice slight changes). A modification of the MIP proof was required to achieve polynomial time in (iii); the earlier technique yields N“(*OglOg’1 time only. This result becomes significant if software and hardware reliability are regarded aa a considerable cost factor. The polylogarithmic checker is the only part of the system that needs to be trusted; it can be hard wired. (We use just one Checker for all problems!) The checker is tiny and so presumably can be optimized and checked off-line at a modest cost. In this setup, a single reliable PC can monitor the operation of a herd of supercomputers working with possibly extremely powerful but unreliable software and untested hardware. 1Research partially supported by NSF Grant CCR-871OO78. Email: laci@cs.uchicago. edu 2Rese~& partiay supported by NSF Grant CCR-SMXI$XEK5. E-mail: fortnow@cs.uc&cago. edu 3Supported by NSF grant CCR-SJC115276. E-mail: Lnd@cs.bu.edu 4111 cummington St., Boston MA 02215. 5E-mail: mario@cs.uchicago .edu ~1100 E 58th St, Chicago IL 60637. Permission to copy without fee all or part of this msterisl is granted provided that tie copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee snd/or specific permission. @ 1991 ACM 089791-397-31911000410021 $1.50 Leonid A. Levin 3
TL;DR: An attempt is made to identify important subclasses of NC and give interesting examples in each subclass, and a new problem complete for deterministic polynomial time is given, namely, finding the lexicographically first maximal clique in a graph.
Abstract: The class NC consists of problems solvable very fast (in time polynomial in log n ) in parallel with a feasible (polynomial) number of processors. Many natural problems in NC are known; in this paper an attempt is made to identify important subclasses of NC and give interesting examples in each subclass. The notion of NC 1 -reducibility is introduced and used throughout (problem R is NC 1 -reducible to problem S if R can be solved with uniform log-depth circuits using oracles for S ). Problems complete with respect to this reducibility are given for many of the subclasses of NC . A general technique, the “parallel greedy algorithm,” is identified and used to show that finding a minimum spanning forest of a graph is reducible to the graph accessibility problem and hence is in NC 2 (solvable by uniform Boolean circuits of depth O (log 2 n ) and polynomial size). The class LOGCFL is given a new characterization in terms of circuit families. The class DET of problems reducible to integer determinants is defined and many examples given. A new problem complete for deterministic polynomial time is given, namely, finding the lexicographically first maximal clique in a graph. This paper is a revised version of S. A. Cook, (1983, in “Proceedings 1983 Intl. Found. Comut. Sci. Conf.,” Lecture Notes in Computer Science Vol. 158, pp. 78–93, Springer-Verlag, Berlin/New York).
TL;DR: This is the first deterministic algorithm for MIS whose running time is polylogarithmic and whose processor-time product is optimal up to a polylogARithmic factor.
Abstract: A new parallel algorithm for the maximal independent set problem (MIS) is constructed. It runs in O(log4 n) time when implemented on a linear number of EREW-processors. This is the first deterministic algorithm for MIS whose running time is polylogarithmic and whose processor-time product is optimal up to a polylogarithmic factor.
TL;DR: A general framework is developed for removing randomness from randomized NC algorithms whose analysis uses only polylogarithmic independence, and one application is an NC algorithm for the set discrepancy problem, which can be used to obtain many other NC algorithms, including a better NC edge-coloring algorithm.
Abstract: A general framework is developed for removing randomness from randomized NC algorithms whose analysis uses only polylogarithmic independence. Previously, no techniques were known to determinize those RNC algorithms depending on more than constant independence. One application of the techniques is an NC algorithm for the set discrepancy problem, which can be used to obtain many other NC algorithms, including a better NC edge-coloring algorithm. As another application an NC algorithm for the hypergraph coloring problem is provided. >
TL;DR: It is shown that nubots is capable of simulating Boolean circuits of polylogarithmic depth and polynomial size, and this result implies that nubs is a highly parallel model of computation in a formal sense.
Abstract: We study the computational complexity of the recently proposed nubots model of molecular-scale self-assembly. The model generalizes asynchronous cellular automaton to have non-local movement where large assemblies of molecules can be moved around, analogous to millions of molecular motors in animal muscle effecting the rapid movement of large arms and legs. We show that nubots is capable of simulating Boolean circuits of polylogarithmic depth and polynomial size, in only polylogarithmic expected time. In computational complexity terms, any problem from the complexity class NC is solved in polylogarithmic expected time on nubots that use a polynomial amount of workspace. Along the way, we give fast parallel algorithms for a number of problems including line growth, sorting, Boolean matrix multiplication and space-bounded Turing machine simulation, all using a constant number of nubot states monomer types. Circuit depth is a well-studied notion of parallel time, and our result implies that nubots is a highly parallel model of computation in a formal sense. Thus, adding a movement primitive to an asynchronous non-deterministic cellular automation, as in nubots, drastically increases its parallel processing abilities.