Simulating and Compiling Code for the Sequential Quantum Random Access Machine

We consider the problem of storing an n element subset S of a universe of size m, so that membership queries (is x in S?) can be answered efficiently. The model of computation is a random access machine with the standard instruction set (direct and indirect addressing, conditional branching, addition, subtraction, and multiplication). We show that if s memory registers are used to store S, where n <= s <= m/n^epsilon, then query time Omega(log n) is necessary in the worst case. That is, under these conditions, the solution consisting of storing S as a sorted table and doing binary search is optimal. The condition s <= m/n^epsilon is essentially optimal; we show that if n + m/n^o(1) registers may be used, query time o(log n) is possible.

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On the difference between Turing machine time and random-access machine time

Proceedings of ICCI'93: 5th International Conference on Computing and Information ◽

10.1109/icci.1993.315406 ◽

2002 ◽

Cited By ~ 1

Author(s):

K.W. Regan

Keyword(s):

Turing Machine ◽

Random Access ◽

Machine Time ◽

Random Access Machine ◽

The Difference

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A Simple Optimal Parallel Algorithm for Reporting Paths in a Tree

Parallel Processing Letters ◽

10.1142/s0129626497000036 ◽

1997 ◽

Vol 07 (01) ◽

pp. 3-11 ◽

Cited By ~ 1

Author(s):

Andrzej Lingas ◽

Anil Maheshwari

Keyword(s):

Parallel Algorithm ◽

Random Access ◽

Input Tree ◽

Single Pair ◽

Random Access Machine ◽

Erew Pram ◽

Parallel Random Access Machine ◽

Path Queries

We present optimal parallel solutions to reporting paths between pairs of nodes in an n-node tree. Our algorithms are deterministic and designed to run on an exclusive read exclusive write parallel random-access machine (EREW PRAM). In particular, we provide a simple optimal parallel algorithm for preprocessing the input tree such that the path queries can be answered efficiently. Our algorithm for preprocessing runs in O( log n) time using O(n/ log n) processors. Using the preprocessing, we can report paths between k node pairs in O( log n + log k) time using O(k + (n + S)/ log n) processors on an EREW PRAM, where S is the size of the output. In particular, we can report the path between a single pair of distinct nodes in O( log n) time using O(L/ log n) processors, where L denotes the length of the path.

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A Parallel Random Access Machine (PRAM) Model for English Language Recognizer (PRAM-ELR)

International Journal of Computer Applications ◽

10.5120/20749-3139 ◽

2015 ◽

Vol 118 (6) ◽

pp. 12-18

Author(s):

Madiha KhurramPasha ◽

Maryam Feroze ◽

Khurram Ahmad Pasha

Keyword(s):

English Language ◽

Random Access ◽

Random Access Machine ◽

Pram Model ◽

Parallel Random Access Machine

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Transforming Comparison Model Lower Bounds to the PRAM

BRICS Report Series ◽

10.7146/brics.v2i10.19513 ◽

1995 ◽

Vol 2 (10) ◽

Author(s):

Dany Breslauer ◽

Devdatt P. Dubhashi

Keyword(s):

Decision Tree ◽

Lower Bounds ◽

Random Access ◽

Decision Tree Model ◽

Tree Model ◽

Machine Model ◽

Comparison Model ◽

Random Access Machine ◽

Input Domain ◽

Parallel Random Access Machine

This note provides general transformations of lower bounds in Valiant's parallel comparison decision tree model to lower bounds in the priority concurrent-read concurrent-write parallel-random-access-machine model. The proofs rely on standard Ramsey-theoretic arguments that simplify the structure of the computation by restricting the input domain. The transformation of comparison model lower bounds, which are usually easier to obtain, to the parallel-random-access-machine, unifies some known lower bounds and gives new lower bounds for several problems.

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