# Efficient Circuit Simulation in MapReduce

## TL;DR

This paper establishes a theoretical connection between the computational power of MapReduce and Boolean circuit models, showing that many problems in NC can be efficiently solved in MapReduce with constant rounds.

## Contribution

It develops a simulation technique that relates NC complexity classes to MapReduce, demonstrating that NC problems can be solved in a constant number of rounds within MapReduce.

## Key findings

- NC problems can be simulated in MapReduce in O(T(n)/log n) rounds
- NC^(i+1) is contained in DMRC^i for all i
- Problems like integer multiplication and division are solvable in constant MapReduce rounds

## Abstract

The MapReduce framework has firmly established itself as one of the most widely used parallel computing platforms for processing big data on tera- and peta-byte scale. Approaching it from a theoretical standpoint has proved to be notoriously difficult, however. In continuation of Goodrich et al.'s early efforts, explicitly espousing the goal of putting the MapReduce framework on footing equal to that of long-established models such as the PRAM, we investigate the obvious complexity question of how the computational power of MapReduce algorithms compares to that of combinational Boolean circuits commonly used for parallel computations. Relying on the standard MapReduce model introduced by Karloff et al. a decade ago, we develop an intricate simulation technique to show that any problem in NC (i.e., a problem solved by a logspace-uniform family of Boolean circuits of polynomial size and a depth polylogarithmic in the input size) can be solved by a MapReduce computation in O(T(n)/ log n) rounds, where n is the input size and T(n) is the depth of the witnessing circuit family. Thus, we are able to closely relate the standard, uniform NC hierarchy modeling parallel computations to the deterministic MapReduce hierarchy DMRC by proving that NC^(i+1) is contained in DMRC^i for all natural i, including 0. Besides the theoretical significance, this result that has important applied aspects as well. In particular, we show for all problems in NC^1---many practically relevant ones such as integer multiplication and division, the parity function, and recognizing balanced strings of parentheses being among these---how to solve them in a constant number of deterministic MapReduce rounds.