Data parallelism (also known as loop-level parallelism) is a form of parallelization of computing across multiple processors in parallel computing environments. Data parallelism focuses on distributing the data across different parallel computing nodes. It contrasts to task parallelism as another form of parallelism.
Read more about Data Parallelism: Description, Example
Famous quotes containing the words data and/or parallelism:
“Mental health data from the 1950’s on middle-aged women showed them to be a particularly distressed group, vulnerable to depression and feelings of uselessness. This isn’t surprising. If society tells you that your main role is to be attractive to men and you are getting crow’s feet, and to be a mother to children and yours are leaving home, no wonder you are distressed.”
—Grace Baruch (20th century)
“The secret of heaven is kept from age to age. No imprudent, no sociable angel ever dropt an early syllable to answer the longings of saints, the fears of mortals. We should have listened on our knees to any favorite, who, by stricter obedience, had brought his thoughts into parallelism with the celestial currents, and could hint to human ears the scenery and circumstance of the newly parted soul.”
—Ralph Waldo Emerson (1803–1882)