This article explains the fundamental role of CPU cache in bridging the speed gap between processors and memory, covering cache hierarchy, locality principles, write policies, coherence protocols, and practical code optimizations such as data alignment and loop restructuring to improve performance.
This article explains Linux CPU cache architecture—from physical and logical cores, through L1/L2/L3 hierarchy and cache‑line basics, to write‑through/write‑back policies and coherence mechanisms—while demonstrating practical analysis with Valgrind and perf tools.
This article explains why CPU caches are needed, describes the hierarchy and internal structure of cache lines, compares direct‑mapped, set‑associative and fully‑associative caches, and shows how cache‑aware coding can dramatically improve program execution speed.
This article explains the purpose of CPU caches, describes their hierarchical structure and internal organization—including direct‑mapped, set‑associative, and fully‑associative designs—and shows how cache‑aware programming can dramatically speed up matrix operations.
This article explains the purpose of CPU caches, their hierarchical structure and internal designs—including direct‑mapped, set‑associative, and fully‑associative caches—and demonstrates how understanding cache behavior can dramatically improve program performance, illustrated with C++ traversal benchmarks.
This article provides an in‑depth technical analysis of AMD’s RDNA 2 GPU architecture, comparing its compute units, cache hierarchy, latency and bandwidth characteristics with Nvidia’s Ampere, and evaluates real‑world game performance in titles such as Cyberpunk 2077, Titanic Honor & Glory, and Gunner HEAT PC.
This article explains CPU cache levels, cache line concepts, coherence protocols, and how cache‑friendly or cache‑unfriendly code patterns—including false sharing and stride access—affect program performance on modern multicore processors.
