Refining Core Development Skills
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Refining Core Development Skills

Fei has over 10 years of development experience at Tencent and Sogou. Through this account, he shares his deep insights on performance.

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Refining Core Development Skills
Refining Core Development Skills
Feb 27, 2025 · Fundamentals

Inspecting Server Memory Hardware Details with dmidecode

This article explains how software developers can use the Linux dmidecode command to retrieve detailed server memory hardware information, including size, type, speed, bit width, ECC, channel placement, and rank, and interprets the output to better understand the underlying hardware.

DDR4dmidecodehardware
0 likes · 9 min read
Inspecting Server Memory Hardware Details with dmidecode
Refining Core Development Skills
Refining Core Development Skills
Feb 19, 2025 · Operations

Linux Kernel Memory Detection via E820 Mechanism

This article explains how the Linux kernel detects physical memory during boot by leveraging the E820 mechanism, where firmware reports memory ranges via interrupt 15H, enabling the kernel to map usable memory addresses for subsequent allocation.

Boot ProcessE820Linux kernel
0 likes · 8 min read
Linux Kernel Memory Detection via E820 Mechanism
Refining Core Development Skills
Refining Core Development Skills
Oct 22, 2024 · Operations

netcap: An eBPF‑Based Next‑Generation Kernel Network Capture Tool

netcap is an open‑source eBPF‑driven kernel network packet capture tool that extends tcpdump syntax to trace skb‑related functions across the Linux network stack, offering detailed packet tracing, customizable filters, multi‑trace aggregation, and user‑defined output to improve debugging of packet loss and performance issues.

Packet CaptureeBPFnetcap
0 likes · 9 min read
netcap: An eBPF‑Based Next‑Generation Kernel Network Capture Tool
Refining Core Development Skills
Refining Core Development Skills
Sep 21, 2024 · Artificial Intelligence

Using GLM-4-Plus Large Model API: Features, Code Samples, and Practical Application Scenarios

This article introduces the rapid rise of large language models, highlights the advantages of the GLM-4-Plus model—including superior language understanding, long‑text handling, and enhanced reasoning—explains how to obtain API credentials, demonstrates request parameters and curl examples, and showcases diverse real‑world use cases such as code generation, social‑media copy, travel planning, and interview question creation.

API usageGLM-4-Pluscode generation
0 likes · 17 min read
Using GLM-4-Plus Large Model API: Features, Code Samples, and Practical Application Scenarios