October 2000
Intermediate to advanced
288 pages
9h 22m
English
book
Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences
by Albert Y. Zomaya, Fikret Ercal, Stephan Olariu
Content preview from Solutions to Parallel and Distributed Computing Problems: Lessons from Biological SciencesBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
9.4 SCHEDULING TASKS TO A HOMOGENEOUS SYSTEM
In this section, we introduce a parallel genetic algorithm for scheduling tasks to homogeneous systems. Throughout this section, we assume the target architecture is homogeneous; that is, a task takes the same amount of time to execute on any processor. Heterogeneity is discussed in Section 9.5.
We formulate the scheduling problem in a genetic search framework based on the observation that if the tasks of a parallel program are arranged properly in a list, an optimal schedule can be obtained by scheduling the tasks one by one according to their order in the list. With this concept, we encode each chromosome to be a valid scheduling list, one in which the precedence constraints among tasks are preserved. We also introduce two genetic operators: the order crossover and mutation. These operators effectively combine the good features of existing scheduling lists to form better lists. This scheduling algorithm, called parallel genetic scheduling (PGS), is a parallel genetic algorithm. Parallelization is done by partitioning the population into multiple disjoint subpopulations that communicate periodically to exchange the best chromosomes. Using random task graphs for which optimal schedules are known, we have found that the PGS algorithm can generate optimal solutions for a majority of the test cases. Below we describe below the detailed algorithm characteristics and the performance.
9.4.1 Genetic Formulation
Although it has not been proved ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.