Floating-point errors are unavoidable, but how you detect and handle them can make the difference between clean, high-performance C++ code and a debugging nightmare. In this article, we explore the practical techniques for handling NaNs, infinities, and other FP errors — from manual checks to sticky bits and hardware traps — and reveal which approaches actually work without sabotaging performance.
For most of my career I lived in the world of C and C++, and I honestly believed that these languages are the pinnacle of software performance. But two months ago I started working at Azul, the maker of low-latency Java compiler and I had an opportunity to deep dive into Java performance. And it…
At Johnny’s Software Lab we’ve spent a lot of time deep-diving into advanced performance topics — vectorization, cache hierarchies, memory bandwidth, you name it. But not everyone is ready to jump straight into assembly listings and microarchitectural details. This post is for the beginners. For the fresh graduates and junior developers who are just starting…
We’ve discussed SIMD and vectorization extensively on this blog, and it was only a matter of time before SIMD (or vector) functions came up. In this post, we explore what SIMD functions are, when they are useful, and how to declare and use them effectively. A SIMD function is a function that processes more than…
Does it matter if we are compiling with optimizations off (O0) or optimizations on (O3) if the problem is memory bound? Let’s find out…
Copying data can be expensive in some cases, especially since it it doesn’t change the data, it’s just moves it. Therefore we, engineers interested in performance, want to avoid copying data as much as possible. We already talked about avoiding data copying in C++ earlier. In that post, we talked about what mechanism C++ has…
We debug our performance problem by simulating it with llvm-mca!
This is the last memory optimization that we are covering in this blog. You can see the full list of all memory subsystem optimization that we covered earlier here. Definitely a read for anyone who is trying to improve performance of memory intensive software. In this post, we are covering a few remaining optimization techniques…
In this post we investigate methods to speed up convergence loops – while loops that slowly converge to the correct result.
In this post we talk about memory mechanism that increase memory accesses latency and we explore the techniques to avoid them in latency-sensitive systems.
