Memory management can be challenge enough on traditional data sets, but when big data enters the picture, things can slow way, way down. A new programming language announced by MIT this week aims to remedy that problem, and so far it’s been found to deliver fourfold speed boosts on common algorithms.
The principle of locality is what governs memory management in most computer chips today, meaning that if a program needs a chunk of data stored at some memory location, it’s generally assumed to need the neighboring chunks as well. In big data, however, that’s not always the case. Instead, programs often must act on just a few data items scattered across huge data sets.
