This is a soft, and probably also an opinion based question.
Suppose I am writing a library for numeric linear algebra for the purposes of working with financial data. My goals are:
- Since I work with big data, I want to make it as fast as possible by using parallel computing.
- I want my colleagues to use this library without understanding/tweaking the parallelism underneath the functions.
The resulting questions are:
- Is this a good idea to make parallelism the default behaviour? For instance
sum(vector)to parallelise the summation without asking the user.
- If yes, is there any rule of thumb that would cover the default behaviour of the task split between the processors? I.e. how many processors I should use?
Asking on QuantFinance since I am especially interested on how people in the industry tackle this. Thanks in advance.