When people start working with high performance computing or parallel systems, “memory” often sounds like a background detail. It’s not. The way memory is structured can completely change how your applications behave, scale, and even fail. Let’s break it down in a practical way. ⸻ What is Shared Memory? In a shared memory system, all processors access the same memory space. Think of it like multiple people working on a single Google Doc. Everyone sees the same data, and changes are immediately visible. Key traits: One global memory space Fast communication between threads Easier to program (generally) Requires synchronization (locks, semaphores) Where you see it: Multi core CPUs OpenMP based applications Single node parallel jobs The catch: Shared memory doesn’t scale well forever. As you add more cores, contention increases. Memory bandwidth becomes a bottleneck, and performance starts to drop. ⸻ What is Distributed Memory? In distributed memory systems, each processor (or node) has its own private memory.…