The talk is an introduction to programming in Julia and it constructed around hands-on example of its usage. The material is selected in order to help the participants learn when Julia can be a language of choice for solving practical problems. No previous knowledge of Julia is required. Similarities and differences to Python and R will be discussed.
Julia programming language tries to solve problem of delivering a flexible dynamic language, appropriate for scientific and numerical computing, with performance comparable to traditional statically-typed languages.
The talk will discuss in particular: 1. How Julia was designed to allow C-level execution speed? 2. What are benefits and costs of such design? 3. Performance of Julia vs R and Python; in particular comparison to Numba .
In order to keep the talk practical all concepts will be discussed using a typical numerical computing task from quantitative finance - pricing of Asian options.
The presentation will be concluded by discussion of current state of Julia language ecosystem and its readiness for deployment in production solutions.