MIT’s New Tool Predicts How Fast a Chip Can Run Your Code

Folks at the Massachusetts Institute of Technology (MIT) have developed a new machine learning-based tool that will tell you how fast a code can run on various chips. This will help developers tune their applications for specific processor architectures. From a report: Traditionally, developers used the performance model of compilers through a simulation to run basic blocks — fundamental computer instruction at the machine level — of code in order to gauge the performance of a chip. However, these performance models are not often validated through real-life processor performance. MIT researchers developed an AI model called Ithmel by training it to predict how fast a chip can run unknown basic blocks. Later, it was supported by a database called BHive with 300,000 basic blocks from specialized fields such as machine learning, cryptography, and graphics. The team of researchers presented a paper [PDF] at the NeuralIPS conference in December to describe a new technique to measure code performance on various processors. The paper also describes Vemal, a new automatically generating algorithm that can be used to generate compiler optimizations.