Random distributions are not one-size-fits-all (part 2.5)

I recently realized that I could try to implement the reuse-oriented distributions from part 2 using libdivide instead of native (hardware) division (modulo).

Random distributions are not one-size-fits-all (part 2)

In this part, we will look at different algorithms for generating uniformly distributed random numbers and determine whether they fit specific use cases better than Lemire's algorithm.

Random distributions are not one-size-fits-all (part 1)

Recently I was again on CppCast, and again I talked about C++'s standard library support for random numbers. One of the things I said was that random distributions are not one-size-fits-all. This post is about how this applies to Lemire's algorithm for generating uniformly distributed integers.

The Little Things: The Missing Performance in std::vector

`std::vector` is often said to be the default container, because it provides good baseline performance for common operations. Recently, I experimented with a simple API change that can improve the performance of a common usage pattern by 10+ %.

Stop talking about Amdahl's law

Without talking about Gustafson's law and the assumptions both make.