by Steve Nadis, Massachusetts Institute of Technology
FEBRUARY 15, 2022
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 MIT, is calling that notion into question, claiming that one can, in fact, have it all. With the new programming language, which they’ve written specifically for high-performance computing, says Amanda Liu, a second-year Ph.D. student at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), “speed and correctness do not have to compete. Instead, they can go together, hand-in-hand, in the programs we write.”
This tensor language has been announced recently and also came out of MIT. Any thoughts about it?