This article explains the core principles of NUMA architecture, how it is deeply integrated into Linux kernel memory management, process scheduling, and system calls, and provides practical commands and real‑world examples to diagnose and optimize NUMA‑related performance issues.
This article explains the fundamentals of Linux CPU affinity, compares soft and hard binding, shows how to use taskset, sched_setaffinity, numactl and cgroup cpuset, and provides real‑world case studies for servers, game frameworks, Nginx and Hadoop clusters.
This article explains the fundamentals of NUMA architecture, why it matters for multithreaded Linux applications, and provides step‑by‑step practical guidance—including kernel internals, memory allocation policies, useful commands, and performance‑monitoring tools—to help developers optimize memory locality and boost overall program efficiency.
This article explains the hardware basis of NUMA, how Linux reads ACPI SRAT/SLIT tables to discover CPU‑memory topology, the kernel functions that initialize NUMA structures, and how tools like numactl can be used to optimize application performance on multi‑node servers.
This article explains NUMA architecture with hyper‑threading, details CPU cache hierarchies and access latencies, and provides Linux tools and practical optimization techniques to improve cache‑hit rates and minimize cross‑NUMA memory delays.
This guide explains NUMA memory hierarchy, shows how to install and use the numactl command, interprets hardware and NUMA statistics, and presents memory allocation strategies to improve performance on multi‑node Linux systems.
This article investigates how large a single Redis instance can be on a 64 GB server, explains the NUMA memory‑allocation trap, and documents experiments that compare unbound versus CPU‑memory‑affinity‑bound deployments, revealing when swap and OOM occur.
This article documents a hands‑on experiment that allocates a 50 GB Redis instance on a 64 GB dual‑node machine, explores NUMA behavior, demonstrates how memory affinity can trigger swap, and concludes with practical recommendations for Redis memory sizing and NUMA binding.
This article introduces practical CPU and memory subsystem performance tuning for Kunpeng processors, covering optimization concepts, key parameters, common monitoring tools such as top, perf and numactl, and detailed methods like NUMA binding, prefetch control, timer tuning, TLB page size adjustment, and thread concurrency optimization.
