Concurrency, Parallelism and Performance

Concurrency is where confident code goes to die. Parallel systems do not fail loudly. They degrade, stall, and lie to you while still appearing to work. This category exists because modern computing is parallel whether you like it or not, and misunderstanding that reality is expensive.

This section contains some of my best guides on concurrency, parallelism, synchronization, memory ordering, performance engineering, and the subtle failure modes of modern hardware and software. We go deep into false sharing, cache coherence, atomics, lock free design, NUMA effects, and why scaling often stops far earlier than expected.

You will learn why multitasking is mostly a myth, why adding threads can slow programs down, and why performance benchmarks are incredibly easy to fake accidentally. The focus here is on mental models that help you reason about systems under load rather than cargo cult fixes.

If you build high performance systems, AI infrastructure, real time software, or anything that must scale reliably, this knowledge is not optional.