With a tensor language prototype, “speed and correctness do not have to compete … they can go together, hand-in-hand.”

High-performance computing is needed for an ever-growing number of tasks — such as image processing or various deep learning applications on neural nets — where one must plow through immense piles of data, and do so reasonably quickly, or else it could take ridiculous amounts of time. It’s widely believed that, in carrying out operations of this sort, there are unavoidable trade-offs between speed and reliability. If speed is the top priority, according to this view, then reliability will likely suffer, and vice versa.

However, a team of researchers, based mainly at