scholarly journals A Lock-Free Dynamic-Sized Work-Stealing Algorithm with Steal-Half and Work Sharing

Author(s):  
Abin Thottakara ◽  
Jared Wasserman ◽  
Ebin Scaria

In the paper "Thread Scheduling for Multiprogrammed Multiprocessors", Arora, Blumofe, and Paxton (ABP) implement a work-stealing algorithm using a double-ended queue (or \textit{deque}) to solve the task-scheduling problem. In this paper, we will begin by giving an overview of work-stealing in general and the advantages and disadvantages that their paper provides. Our focuses are to address and rectify a few key disadvantages of their static-sized deque implementation: the potential inefficiency that can occur when multiple stealers attempt to take work from the same thread, the inability of the deque to grow, and a lack of efficient work-balancing. Before explaining our algorithm (and our new data structure), we will explain how our solution solves a different problem than that expressed in "A Dynamic-Sized Nonblocking Work Stealing Deque", how it improves the ABP solution scenario aforementioned, how it provides an alternative answer to the work-balancing algorithm (called "WorkSharingThread") in "The Art of Multiprocessor Programming", and how it differs from the algorithm in the paper "Non-blocking steal-half work queues." Following this, we will delve into the details of our algorithm, informally proving how it can effectively distribute a workload when there are multiple stealers. Finally, we will show the results of our experiments on various workloads, comparing the performance to that of the ABP.

2014 ◽  
Vol 49 (4) ◽  
pp. 513-528
Author(s):  
Haris Ribic ◽  
Yu David Liu

MENDEL ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 179-188
Author(s):  
Abdelhamid Khiat ◽  
Abdelkamel Tari

The independent task scheduling problem in distributed computing environments with makespan optimization as an objective is an NP-Hard problem. Consequently, an important number of approaches looking to approximate the optimal makespan in reasonable time have been proposed in the literature. In this paper, a new independent task scheduling heuristic called InterRC is presented. The proposed InterRC solution is an evolutionary approach, which starts with an initial solution, then executes a set of iterations, for the purpose of improving the initial solution and close the optimal makespan as soon as possible. Experiments show that InterRC obtains a better makespan compared to the other efficient algorithms.


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