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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 PhD 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.”

A new programming language for high-performance computers Researchers at MIT CSAIL developed a new programming language specifically for high-performance computing. With the prototype, says PhD student Amanda Liu, “speed and correctness do not have to compete ... they can go together, hand-in-hand.”