SIMPLE DETERMINISTIC AND RANDOMIZED ALGORITHMS FOR LINKED LIST RANKING ON THE EREW PRAM MODEL
Sajal K. Das, Ranette Halverson
Abstract
Sajal K. Das, Ranette Halverson
Abstract
An asynchronous, CRCW PRAM (or APRAM) algorithm for linked list ranking, proposed by Martel and Subramonian, performs EO (n log log n) expected work employing [Formula: see text] processors. Motivated by their unique approach, this paper proposes two EREW list ranking algorithms – one deterministic and the other randomized. The deterministic algorithm performs in [Formula: see text] time using p processors, where n≥p log p. Thus, for p= O (n/ log n), it requires O ( log n log log n) time and O (n log log n) work. Although not work-optimal, this algorithm is very simple compared to the known work-optimal (deterministic) EREW algorithms for list ranking and has the added advantage of small constant factors in the time and space requirements. The randomized algorithm follows the same line of approach, but uses randomization in one step to decrease the time complexity, thus improving on the time complexity of the original algorithm. It requires [Formula: see text] expected time, and hence it is an EO ( log n) expected time, work-optimal algorithm employing p= O (n/ log n) processors. Furthermore, the randomized algorithm uses less space than the deterministic algorithm.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
An asynchronous, CRCW PRAM (or APRAM) algorithm for linked list ranking, proposed by Martel and Subramonian, performs EO (n log log n) expected work employing [Formula: see text] processors. Motivated by their unique approach, this paper proposes two EREW list ranking algorithms – one deterministic and the other randomized. The deterministic algorithm performs in [Formula: see text] time using p processors, where n≥p log p. Thus, for p= O (n/ log n), it requires O ( log n log log n) time and O (n log log n) work. Although not work-optimal, this algorithm is very simple compared to the known work-optimal (deterministic) EREW algorithms for list ranking and has the added advantage of small constant factors in the time and space requirements. The randomized algorithm follows the same line of approach, but uses randomization in one step to decrease the time complexity, thus improving on the time complexity of the original algorithm. It requires [Formula: see text] expected time, and hence it is an EO ( log n) expected time, work-optimal algorithm employing p= O (n/ log n) processors. Furthermore, the randomized algorithm uses less space than the deterministic algorithm.
Key concepts: Deterministic algorithm, Binary logarithm, Log-log plot, Randomized algorithm, Algorithm, Competitive analysis, Time complexity, Freivalds' algorithm