A Japanese team has increased the speed of parallel computing by using a
genetic algorithm to schedule processing tasks. Tatsuhiro Tsuchiya and
colleagues at Osaka University have designed their evolutionary algorithm to
allow only the “fittest” task sequences—the computer equivalents of
chromosomes—to survive (Microprocessors and Microsystems, vol 22,
p 197). The surviving sequences become the tasks executed by each processor node
in an array. Using task duplication, so that the task can be executed as soon as
a node is free, the algorithm performed as well as—and sometimes
better—than DSH, a common non-genetic task-scheduling system.
More from New ÒÁÈ˾þÃ
Explore the latest news, articles and features
Popular articles
Trending New ÒÁÈ˾þà articles
1
Mathematicians stunned by AI's biggest breakthrough in mathematics yet
2
The Selfish Gene at 50: Why Dawkins’s evolution classic still holds up
3
How I used psychology to come back from the worst year of my life
4
Photos reveal unexpected details from the world's first atomic test
5
Mystery of the ancient giant stone jars of Laos may have been solved
6
The distant world that is our best hope of finding alien life
7
Can we harness quantum effects to create a new kind of healthcare?
8
Why autism pioneer Uta Frith wants to dismantle the spectrum
9
Epic dreaming is leaving people exhausted and distressed
10
Women’s better memories may delay Alzheimer’s diagnosis by years



