The hybrid dynamic parallel scheduling algorithm for load balancing on Chained-Cubic Tree interconnection networks

Abstract

The Chained-Cubic Tree (CCT) interconnection network topology was recently proposed as a continuation for the extended efforts in the area of interconnection networks' performance improvement. This topology, which promises to exhibit the best properties of the hypercube and tree topologies, needs to be deeply investigated in order to evaluate its performance among other interconnection networks' topologies. This work comes as a complementary effort, in which the load balancing technique is investigated as one of the most important aspects of performance improvement. This paper proposes a new load balancing algorithm on CCT interconnection networks. The proposed algorithm, which is called Hybrid Dynamic Parallel Scheduling Algorithm (HD-PSA), is a combination of two common load balancing strategies; dynamic load balancing and parallel scheduling. The performance of the proposed algorithm is evaluated both, analytically and experimentally, in terms of various performance metrics; including, execution time, load balancing accuracy, communication cost, number of tasks hops, and tasks locality.

A Simulation Model for the Performance Evaluation of Hybrid Interconnection Architectures

“…It is not easy to design an algorithm for a system when processing elements share resources and work cooperatively. Chained Cubic Tree (CCT) is considered as hybrid architecture [4]. The author suggested a task scheduling for CCT network and claimed optimal or near optimal solution in scheduling and executing the tasks.…”

Adaptive Load Balancing Dashboard in Dynamic Distributed Systems

“…A lot of studies were conducted to find a proper algorithm. In [9] authors propose a dynamic parallel scheduling algorithm for load balancing. Several strategies are proposed to distribute the load using dynamic and distributed load balancing mechanisms, called sender-initiated and receiver-initiated strategies.…”

An unfair semi-greedy real-time multiprocessor scheduling algorithm

“…In line 28, the task Id of the processor is updated to the Id of the zero laxity task (Tw). Now, both tasks are ready to be replaced, and thus, task (Tw) is added to heap H R , while task (Tr) is added to heap H W (lines [29][30]. The while loop in line 21 then continues until all Z events are handled.…”

“…time slices as mentioned previously, which are bounded by two successive deadlines, and the end of each TL-plane corresponds to the deadline of a task in the system. Hence, tasks are marshalled in the intervals [0, 5), [5,7), [7,10), [10,14), [14,15), [15,16), [16,17), [17,19), [19,20), [20,21), [21,25), [25,26), [26,28), and [28,29), which correspond to the first 14 TL-planes, after which all tasks would finish at least one period of their executions. This means that at the beginning of each TL-plane, all tasks have to be allocated local executions proportional to their utilizations and marshalled until the end of the time slice at which they must all be preempted.…”