Systems Programming and Computer Architecture

Abstractions are useful until they lie to you. When performance collapses, latency spikes, or systems behave impossibly, the answers live below the surface. This category is about understanding computers as they actually exist, silicon, memory, instructions, and constraints.

This section contains some of my best guides on systems programming, memory management, CPU architecture, operating system behavior, and the physical realities that shape software performance. We talk about caches, pipelines, branch predictors, SIMD, virtual memory, allocators, system calls, and the brutal economics of data movement.

You will learn why modern CPUs execute instructions out of order, why memory is never as fast as you think it is, and why just adding hardware often makes things worse. I cover RISC V, ARM, x86, accelerators, and the architectural tradeoffs driving modern computing, especially in an AI dominated world.

This is not nostalgia for low level programming. It is about leverage. Engineers who understand the machine beneath the code build faster systems, debug impossible bugs, and see through performance myths instantly.