This guide walks through a systematic troubleshooting workflow for a Linux gateway that spikes to 891% CPU, using top to locate the offending process, inspecting thread usage, capturing stack traces with gstack, dumping core files, tracing system calls with strace, and analyzing the core dump in gdb to pinpoint the poll() call causing the load.
This article explains how dynamic rate limiting can automatically compute throttling thresholds using system load metrics such as CPU usage, load average, and response time, and demonstrates its effectiveness through real‑world testing on a flight‑price service.
This article introduces four Python CPU profiling tools—cProfile, line_profiler, pprofile, and vprof—explaining their installation, usage on CPython and PyPy, interpreting their outputs, and visualizing results with graphviz, helping developers identify performance bottlenecks such as costly list.append calls.
The article explains why general‑purpose CPUs can no longer meet deep‑learning demands due to intrinsic scaling limits and memory‑bandwidth bottlenecks, and surveys how heterogeneous accelerators—GPUs, FPGAs, ASICs and emerging AI processors with high‑bandwidth memory—provide specialized, high‑parallelism, power‑efficient solutions for both cloud and edge workloads.
The article analyzes the limitations of general‑purpose CPUs for deep‑learning workloads, explains how semiconductor scaling and memory‑bandwidth constraints drive the shift toward specialized heterogeneous processors such as GPUs, FPGAs, and ASICs, and discusses the design trade‑offs of embedded versus cloud AI accelerators.
A customer’s Oracle 11g RAC experienced chronic high CPU usage; deep AWR analysis revealed that massive parse time was attributed to mutex waits and a hidden hard‑parse failure caused by a missing column, which triggered Bug 16175381 and forced process spin, ultimately resolved by correcting the faulty SQL.
This guide explains how to assess and improve server performance by understanding key metrics such as CPU utilization, memory management, and disk I/O, introducing fundamental concepts, analysis methodologies like 5W2H and load‑characteristic summarization, and recommending practical Linux tools such as uptime, vmstat, top, perf, and DTrace for comprehensive troubleshooting.
This article provides a comprehensive guide to server performance optimization, covering the fundamentals of CPU, memory, and I/O analysis, practical methodologies, essential tools, and real‑world case studies to help operations engineers identify bottlenecks and improve system stability.
A production MySQL incident showed sudden system CPU spikes and many running threads despite low query throughput, which was traced to the server's time_zone=system setting causing timestamp conversion to lock a global mutex, leading to excessive spin‑locks, context switches, and degraded performance that was resolved by changing the time_zone to a fixed offset.
This article explains the fundamentals of web animation performance, examines a complex canvas‑based weather animation case, introduces tools like Chrome's FPS meter and stats.js, and details browser rendering pipelines, CPU/GPU roles, and practical optimization techniques for smoother front‑end experiences.
This article explains three Android CPU performance testing techniques—using adb dumpsys cpuinfo, reading /proc/pid/stat, and employing the top command—detailing their procedures, advantages, limitations, and how to aggregate per‑process data for accurate app‑level metrics.
This article walks through the complete semiconductor manufacturing flow, from raw quartz to polished silicon wafers, photolithography, ion implantation, metal deposition, testing, die cutting, packaging, and final grading, revealing why CPUs are the most integrated, un‑replicable chips in modern technology.
This article provides a detailed tutorial on measuring and optimizing iOS app performance, covering startup and load times, memory and CPU usage, smoothness metrics, and practical code snippets using Apple Instruments and other tools to obtain reliable data across devices.
This article outlines practical Linux‑based optimization techniques for MySQL, covering CPU power‑saving modes, NUMA and vm.swappiness settings, as well as mount options and I/O scheduler tweaks to maximize database throughput and stability.
This article describes how adjusting the PHP‑FPM max_requests setting and modifying its source code can smooth CPU idle and memory usage fluctuations in a high‑traffic online service, improving resource stability and reliability.
This article provides a detailed chronological overview of the rivalry between Intel and AMD, covering their shared origins, early collaborations with IBM, legal battles, the rise of AMD’s Athlon and 64-bit processors, Intel’s Tick‑Tock strategy, and the evolving market dynamics that shaped modern CPU architecture.
This guide presents comprehensive Oracle database performance optimization techniques—including data structure design, application architecture, SQL tuning, memory and CPU adjustments, I/O balancing, and essential tools—providing actionable steps and example queries for DBAs to improve system responsiveness and efficiency.
Hardware acceleration in Android shifts intensive floating‑point UI work from the CPU to the GPU by building DisplayLists on the CPU and rasterizing them on the GPU, allowing parallel processing, selective redraw of unchanged elements, and significantly higher frame rates for animations and complex graphics.
This article explains common Android performance problems such as battery drain, slow startup, and lag, and provides step‑by‑step instructions for measuring memory and CPU usage using adb commands, Android Studio tools, and the ActivityManager.MemoryInfo API.
This article provides a detailed, step‑by‑step guide for iOS developers on measuring and optimizing app performance across CPU usage, GPU‑related stutter, network conditions, and energy consumption using built‑in Instruments, Activity Monitor, Network Link Conditioner, and Charles.
This article walks through a real‑world remote debugging session where a high‑CPU issue in a gateway service was reproduced, analyzed with top, gstack, gcore, strace and gdb, and traced to a buffer overflow causing an infinite loop, then fixed.
This article explains how to identify and resolve intermittent high CPU usage in Java/Tomcat services by analyzing thread stacks with jstack, examining GC behavior with Jstat, and using Jmap for memory inspection, providing step‑by‑step commands and practical tips for ops engineers.
This article introduces the Linux sar command, explains its syntax and common options, and demonstrates how to sample and interpret CPU, memory, I/O, process queue, and swap metrics to identify system bottlenecks during performance testing.
This article outlines comprehensive mobile performance testing practices for Baidu Video, covering background, key performance dimensions such as smoothness, crash, memory, power, CPU, and network, and detailing metric collection methods on Android and iOS using command‑line tools, Xcode Instruments, and third‑party utilities.
This article explains practical methods for measuring iOS app performance—including startup time, page load, memory, CPU and smoothness—by instrumenting code, using Apple Instruments tools, analyzing webview loading, and employing runtime techniques such as dynamic library hooking and script‑driven profiling.
This article provides a comprehensive overview of the Linux sar command, explaining its syntax, common options, example use‑cases for CPU, memory, I/O and process monitoring, and how to interpret the output fields to identify system bottlenecks.
This article explains which external and internal performance metrics matter for backend services, how to interpret them, common bottlenecks, and provides a step‑by‑step example using JMeter to measure throughput, latency, CPU, memory, load, network and disk I/O.
This guide walks through Linux Container (LXC) resource management, explaining how to control CPU, memory, and storage using cgroup commands, configuration files, and monitoring tools, with step‑by‑step examples and practical tips for efficient container operation.
This article provides a comprehensive visual overview of CPU architecture, instruction sets, operating system purposes, programming layers, privilege rings, execution modes, user interfaces, and the distinction between ABI and API, helping readers grasp core computing concepts in a structured manner.
Through a whimsical first‑person narrative, the article walks readers through a CPU’s start‑up sequence, BIOS interrupt handling, loading the boot sector, memory access patterns, the principle of locality, cache usage, and the introduction of pipelining to illustrate fundamental computer architecture concepts.
A MySQL replica was consuming an entire CPU core due to single‑process replication, and analysis of binlog and InnoDB status revealed heavy row locks on a table without a primary key, which was resolved by adding an auto‑increment ID, dropping CPU usage to 3% and eliminating replication lag.
This article analyzes why the browser engine's CPU usage does not converge to zero when a page becomes invisible or the app is backgrounded, presents a lightweight testing methodology, identifies dynamic‑element and Blink‑kernel bugs, and proposes concrete fixes that restore proper CPU convergence.
A detailed case study shows how a 1% precision difference discovered by query‑diff testing was traced to CPU instruction‑set discrepancies (AVX vs SSE), highlighting the impact of hardware‑level floating‑point optimizations on algorithmic results and providing practical debugging and mitigation guidelines.
This article details a query‑diff test that revealed a 1% floating‑point precision difference after a module upgrade, describes the systematic investigation of environment, compilation, and CPU instruction‑set variations (AVX vs SSE), and presents conclusions and recommendations for preventing similar issues.
This guide walks IT operations engineers through systematic Linux‑based techniques for pinpointing Java processes that consume excessive CPU or memory, using tools like top, ps, jstack and jmap, and provides concrete steps to analyze and remediate the underlying code.
This article explores the challenges of real‑time HTML and inline JS/CSS minification with html‑minifier in Node.js, including CPU‑spike bugs caused by malformed HTML, workarounds using the vm module with timeouts, performance optimizations, and future directions for faster, stable compression.
This article examines why modern web systems face exploding concurrent connections, explains how richer pages and browser limits increase load, and presents front‑end caching, request merging, Apache/Nginx memory and CPU optimizations, and practical guidelines for reducing server resource consumption.
This guide explains how to enable MySQL’s Query Profiler, retrieve summary and detailed profiling data, and analyze CPU and I/O usage to pinpoint performance bottlenecks in your queries, including commands to list profiles, view specific query details, and interpret the results for optimization.
This guide explains how to use the Linux vmstat command to monitor system performance, detailing its output fields such as process states, memory, swap, I/O, system interrupts, and CPU usage, and shows how to interpret each metric for effective troubleshooting.
Load average measures the average number of processes waiting for CPU over 1, 5, and 15 minutes, differing from CPU utilization; this article explains the concepts, ideal values, illustrative analogies, and practical steps to assess and reduce server CPU load for better performance.
This guide lists thirteen Linux commands and tools—including /proc/cpuinfo, cpufreq-info, cpuid, dmidecode, hardinfo, i7z, likwid, lscpu, lshw, lstopo, numactl, and x86info— that reveal comprehensive CPU hardware information such as vendor, model, frequencies, cores, caches, and topology.
The article explains how web front‑end optimization, including static site generation, relies on improving browser‑server performance by addressing CPU, storage, and especially network bottlenecks, and argues that front‑end engineers should view themselves as browser‑application experts rather than just HTML/CSS/JS coders.
This guide walks through identifying a Java process that spikes CPU usage, locating the offending thread with Linux tools, extracting its stack trace, pinpointing the problematic code in a socket utility class, and outlining the steps to resolve the infinite‑loop issue.
