Every programmer should know about memory because memory access is a critical bottleneck in modern computing systems. Key concepts include understanding the hierarchy of memory—from fast and small CPU caches (L1, L2, L3) to slower but larger RAM (DRAM)—and how programs can optimize cache usage to improve performance by leveraging data locality and cache-friendly algorithms. Knowing the differences between SRAM (used in caches) and DRAM (used in main memory), the importance of cache lines, and the impact of architectures like NUMA (Non- Uniform Memory Access) helps developers write efficient code that aligns well with hardware constraints. Additionally, understanding hardware techniques such as prefetching and direct memory access (DMA) can further optimize software speed and efficiency. Tools exist to analyze memory usage and cache performance for fine-tuning applications. Ultimately, this knowledge is vital to harness the full potential of modern multi-core, multi-threaded processors and avoid memory access delays that slow down execution significantly.
