Efficiency

Data are rarely perfect. Robust data science tools must have ways to deal with missing data. However, this is not always easy. A balance must be struck between performance and convenience.

A Galois field is a finite field and are used in a variety of applications, including in classical coding theory and cryptography algorithms. This topic studies how to efficiently optimize arithmetic in such fields.

The LLVM Compiler Infrastructure Project now powers a wide variety of software, including major programming languages including Rust and Julia, as well as compilers for the popular C and C++ programming languages. Understanding how LLVM works, and being able to read some LLVM bytecode, is extremely useful for optimizing code.

Computer science is, fundamentally, about abstraction and efficiency. A programmer would rather use high-level bricks to build a product than worry about low-level details. Regrettably, the use of high-level bricks often comes at a cost in efficiency, forcing programmers to worry about low-level details. Recently, many programming languages have begun to stress the importance of zero-cost abstractions: ways to construct high-level bricks with zero efficiency cost.