MIT Develops Machine-Learning Tool to Make Code Run Faster

MIT researchers have built a new benchmark tool that can accurately predict how long it takes given code to execute on a computer chip, which can help programmers tweak the code for better performance. MIT researchers have invented a machine-learning tool that predicts how fast computer chips will execute code from various applications. To get code to run as fast as possible, developers and compilers -- programs that translate programming language into machine-readable code -- typically use performance models that run the code through a simulation of given chip architectures. Compilers use that information to automatically optimize code, and developers use it to tackle performance bottlenecks on the microprocessors that will run it. But performance models for machine code are handwritten by a relatively small group of experts and are not properly validated.