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).
I recently realized that I could try to implement the reuse-oriented distributions from part 2 using libdivide instead of native (hardware) division (modulo).
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.
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.
`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+ %.
At the end of January, I removed some low-hanging allocations from Catch2. This meant that running the SelfTest binary in v3.3.1 made 8k fewer allocations, but it also made section tracking in v3.3.1 ~4x slower. This post is about how that happened and what we can learn from this.