Waterloo researchers boost Linux kernel for energy efficiency

Linux vs. C: Which Invention Truly Changed Computing? ---------------------------------------------------------------  A Deep Technical Exploration of Language, Architecture, and System Design Introduction — From Programming to Shaping the Digital Reality The history of operating systems is, at its core, the history of controlling hardware. Every operating system is an intelligent layer that manages the CPU, memory, and peripherals, providing an organized interface for programmers. To build such a layer, one needs a language that allows direct access to physical resources without sacrificing abstraction and maintainability. This is precisely where C appeared — a language that balanced low-level control with high-level structure — and two decades later, Linux emerged to prove that such a language could power an open, global operating system. Read more ... https://lnkd.in/dk-qTV5h

Recently, I had the chance to read BPF Performance Tools to brush up on my Linux skills. While exploring, I came across several common CPU troubleshooting tools. I decided to create a runbook a practical guide that I (or anyone like me) can refer to whenever a CPU issue arises. This guide covers which tools to use, how to analyze their output, and how to draw actionable conclusions. Topics covered in the guide: - Understanding what “CPU” means in different environments and basic CPU concepts - Where to start when you encounter CPU issues - Using uptime and interpreting its output - Using top, why it’s useful, and how to analyze its output - Understanding mpstat, when to use it, and how to interpret the results - Tools for deep-diving into CPU issues - When to use profile, offcputime, and runqlen, what insights they provide, and how to connect the dots - Step-by-step implementation in a mini-lab to test these tools on your own **Note: There are many other tools available apart from the ones mentioned here, but I hope this guide will be handy for handling most of our day-to-day CPU issues.** I created this article after reading BPF Performance Tools and with some help from ChatGPT. I wanted to explore the concepts practically and see different scenarios in action. This is my personal take on what I learned, written in my own style — I hope it’s useful for anyone learning CPU troubleshooting. Happy learning! https://lnkd.in/gR_sacqD Thanks for all your motivation Savinder Puri #learning-in-public #Linux-Performance #CPU-Troubleshooting #BPF-tools #System-Monitoring #Linux-Optimization #High-CPU-Usage #SRE-Tools #Linux-Debugging #Performance-analysis

********. Slurm vs. PBS .********* The High-Performance Computing Showdown Choosing the right Workload Manager (WLM) is critical for any serious High-Performance Computing (HPC) environment. For years, PBS (Portable Batch System) and its derivatives like Torque and PBS Pro have been staples. But now, Slurm (Simple Linux Utility for Resource Management) is widely adopted and often the default for new clusters. Why the Shift to Slurm? While both manage resources, schedule jobs, and enforce policies, there are notable differences: 1. Open Source & Community: Slurm is purely open-source with a highly active community, which appeals to many research and academic institutions. PBS Pro, while robust and commercially supported, is proprietary. 2. Syntax & Workflow: Slurm often streamlines the process. For example, batch jobs start in the submission directory automatically, unlike older PBS implementations where you might need cd $PBS_O_WORKDIR. Also, Slurm tends to leverage the kernel's control groups (cgroups) for resource limits more directly. 3. Resource Specification: There are differences in how resources are requested. PBS often focuses on nodes and processors per node (ppn), while Slurm emphasizes tasks and CPUs per task, which can offer more flexibility. The Migration Challenge For teams moving from a legacy PBS/Torque system to Slurm, the real work lies in converting years of submission scripts and getting users accustomed to new commands (e.g., sbatch instead of qsub, squeue instead of qstat). Question for the HPC community: If your cluster has recently migrated from PBS to Slurm, what was the single biggest lesson learned or the most useful conversion script/tool you found? #HPC #HighPerformanceComputing #Slurm #PBS #SystemAdministration #WorkloadManagement

💡 If you use a Raspberry Pi for home projects or remote servers, here’s a pro tip: Set up Dynamic DNS (DDNS) to stay connected — no matter how often your IP changes. Our latest guide walks you through setting up DDNS on Raspberry Pi using No-IP — from hostname creation to port forwarding. Gain reliable, remote access to your Pi for hosting, automation, and more 🔧 ✅ Access your device anywhere ✅ Avoid static IP costs ✅ Boost your DIY project uptime Read the full setup guide 👇 https://lnkd.in/gKKeSt5p

𝗧𝗵𝗲 𝗟𝗶𝗻𝘂𝘅 𝗕𝗼𝗼𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 (𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗱) Ever wondered what actually happens when you press the power button on your Linux machine? From BIOS to login, your system goes through multiple stages before it’s ready for you to use. Here’s how it works:  1. 𝗣𝗼𝘄𝗲𝗿 𝗢𝗻 - The journey begins as your computer wakes up.  2. 𝗕𝗜𝗢𝗦/𝗨𝗘𝗙𝗜 - It runs initial hardware checks (POST) and loads from non-volatile memory.  3. 𝗗𝗲𝘁𝗲𝗰𝘁 𝗗𝗲𝘃𝗶𝗰𝗲𝘀 - CPU, RAM, and storage devices are identified.  4. 𝗖𝗵𝗼𝗼𝘀𝗲 𝗕𝗼𝗼𝘁 𝗗𝗲𝘃𝗶𝗰𝗲 - The system selects where to boot from (HDD, SSD, USB, etc.).  5. 𝗕𝗼𝗼𝘁 𝗟𝗼𝗮𝗱𝗲𝗿 (𝗚𝗥𝗨𝗕) - Loads kernel and essential libraries from /etc/grub2.cfg.  6. 𝗞𝗲𝗿𝗻𝗲𝗹 𝗜𝗻𝗶𝘁𝗶𝗮𝗹𝗶𝘀𝗮𝘁𝗶𝗼𝗻 - The kernel mounts file systems and starts the first process.  7. 𝗦𝘆𝘀𝘁𝗲𝗺𝗱 - Takes over as the first process in user space and runs target files.  8. 𝗦𝘁𝗮𝗿𝘁𝘂𝗽 𝗦𝗰𝗿𝗶𝗽𝘁𝘀 - /etc/profile, .bashrc, and login services run. Users can now log in. 𝗜𝗻 𝘀𝗵𝗼𝗿𝘁: From the moment you power on to the time you log in, Linux orchestrates a precise chain of actions to bring your system to life. If you’re learning Linux or DevOps, understanding this flow helps you troubleshoot faster and think like a system engineer. #linux #devops #systemadmin #cloudcomputing #itfundamentals #grub 

When I joined Bell Laboratories in 1987 some of the mandatory courses for newly inducted Members of Technical Staff included Unix and C with none other than Dennis Ritchie. I found this article in a FaceBook page for Bell Labs alumni and thought I would share it. ≠================ Dennis Ritchie changed the world from a small, cluttered lab at Bell Labs and almost no one noticed. While Steve Jobs and Bill Gates became household names, Ritchie sat behind a terminal in 1971 and quietly built the foundation of modern computing. He co-created Unix, an operating system that would one day run everything from NASA servers to iPhones. Then, as if that weren’t enough, he invented the C programming language, the DNA of nearly every major software system that exists today. There was no press release. No startup. No billionaire fortune. Just elegant code. Ritchie believed good software should outlive its creator. “C is quirky, flawed, and an enormous success,” he once wrote, describing his masterpiece with the understatement of a man who knew exactly what he’d done. Born in 1941 in Bronxville, New York, the son of a Bell Labs scientist, Ritchie studied physics at Harvard before trading equations for algorithms. At Bell Labs in the 1960s, he and Ken Thompson began designing Unix as a way to make computers more democratic—simple, portable, and open. What started as a side project on a discarded machine became the blueprint for every major operating system to follow: Linux, MacOS, Android, even Windows owe their roots to it. Ritchie never chased fame or money. He stayed at Bell Labs for decades, teaching through example that innovation doesn’t need a spotlight. Colleagues said he wrote code like poetry—minimal, clear, and eternal. In 1983, he received the Turing Award, computing’s Nobel Prize. In 2011, he died quietly at home in New Jersey. His passing went largely unnoticed in the media—overshadowed by Steve Jobs’s death a week earlier. Yet without Ritchie, Jobs’s world would not have had an operating system to stand on. Dennis Ritchie, the quiet scientist who taught machines to talk, didn’t sell his ideas—he gave them away. He proved that real revolutionaries don’t need applause; they just need clean code and the courage to let the world build on it.

The Unsung Hero of Modern Computing: How Linux SMP Scales Performance 📈 Dive into the core of high-performance computing, and you'll find the Linux Symmetric Multiprocessing (SMP) architecture. This isn't just about throwing more cores at a problem; it's a sophisticated design challenge within the kernel itself. What is Linux SMP? It's the architecture where two or more identical CPU cores share the same memory and are controlled by a single instance of the Linux OS. In an SMP system, every core is a peer, capable of executing any task—including kernel code. The Engineering Challenge: The true complexity lies in ensuring efficiency and data integrity: Dynamic Load Balancing: The Completely Fair Scheduler (CFS) constantly balances execution across all cores for optimal utilization. Synchronization: Mechanisms like spinlocks and atomic operations prevent race conditions when multiple cores access shared kernel data structures. Cache Coherence: The kernel and hardware must work together (e.g., via the MESI protocol) to ensure consistent data views across all core caches. Understanding these kernel-level concepts is fundamental for anyone working on high-throughput servers, data centers, or robust embedded Linux systems. The efficiency of your infrastructure often boils down to how well the kernel manages its SMP environment. What kernel-level challenge do you find most fascinating? Share your insights! #LinuxKernel #SymmetricMultiprocessing #KernelDevelopment #HighPerformanceComputing #EmbeddedSystems #OperatingSystems #TechTalk

🍵 TechDhaba Byte: 🕰️ RCU Magic — “Readers Eat First, Writers Cook Later” 🍛⏱️ In the grand buffet of the Linux kernel, thousands of readers line up, hungry for data. If every reader waited for the writer to finish cooking, dinner would never start. So how does Linux serve millions of concurrent reads without locking the kitchen? Enter RCU — Read-Copy-Update, the secret recipe behind some of the fastest data access patterns in modern kernels. 🧠 The Idea — Serve First, Cook Later RCU turns synchronization upside-down. Readers don’t wait — they grab the old version of the data immediately. Writers quietly prepare a fresh copy in the background, then swap it in atomically when ready. Once all current readers finish, the old dish (data) is cleared away. No waiting, no fighting — just smooth, coordinated choreography between chefs and diners. ⚙️ Where You’ll Find It in Linux The task scheduler uses RCU to traverse process lists safely. The networking stack relies on RCU for fast routing table lookups. Even VFS (Virtual File System) walks through inode trees using RCU for near-lock-free access. It’s everywhere — quietly scaling Linux across thousands of cores. 🎯 TechDhaba Takeaway ✅ RCU is the ultimate example of grace under pressure — real-time reads, deferred updates. ✅ Perfect when reads dominate writes (think routing tables, process lists, etc.). ✅ Not magic: it relies on memory barriers, grace periods, and careful design. ✅ Writers must cook carefully — readers must know what version they’re eating! 😄 In the kernel’s kitchen, RCU keeps the buffet open 24×7 — everyone eats, no one blocks, and performance stays sizzling. 🔥 Next TechDhaba Byte Preview: 🧩 Memory Models Decoded — “The Invisible Rules of CPU Conversation” Why your CPUs sometimes “lie” about the order of things — and how barriers keep the truth straight. #Linux #Kernel #RCU #Concurrency #Synchronization #LocklessProgramming #Parallelism #PerformanceEngineering #DeviceDrivers #EmbeddedSystems #RTOS #TechDhaba #SystemProgramming #EngineeringLeadership #RaceConditions #MultiCore

A tape-based piece of unique Unix history may have been lying quietly in storage at the University of Utah for 50+ years. The question is whether researchers will be able to take this piece of middle-aged media and rewind it back to the 1970s to get the data off. https://lnkd.in/gmihsGSN

💻 Linux, Kernel, and CPU — How Computers Really Work When I started learning Linux, I kept asking: 👉 When does the OS run? When does the kernel take control? How does the CPU know what to do? Here’s a simple way I now understand it. ⚙️ 1. CPU — The Brain 🧠 The CPU is hardware. It executes instructions and performs calculations. It doesn’t know what programs exist; it waits for the kernel. Modern CPUs have multiple cores to run several tasks at once. 🧩 2. Kernel — The Manager 🕹️ The kernel is the heart of Linux. It connects software to hardware. Its main jobs: 🧮 CPU Scheduling — Decides which program runs next 💾 Memory Management — Allocates RAM safely 📀 Device & Disk Control — Talks to keyboards, GPUs, storage 🌐 System Calls — Lets programs request hardware safely 💡 Fun fact: Linux itself is technically just the kernel. Everything else — apps, desktop — runs on top of it. 💾 3. Memory, Devices, and Disks Memory (RAM) — Workspace for running programs Disks/Storage — Organized by file systems like ext4, btrfs Devices — Keyboard, mouse, network card; kernel uses drivers to control them 💻 4. Operating System — The Full Environment 🌍 The OS = Kernel + Tools + Apps + Interface Examples: Ubuntu, Fedora, Debian, Arch The OS lets humans interact with hardware safely — without touching the CPU directly. 🔄 5. Power-On Workflow 1. Bootloader loads the kernel 2. Kernel initializes CPU, memory, and devices 3. Kernel starts essential processes 4. Disks and file systems are mounted 5. User interface (CLI or GUI) appears The kernel keeps running in the background, managing everything. 🖥️ Example: Running a Command Let’s say you type: $ cat file.txt Here’s what happens: 1. Shell receives your command — you requested cat file.txt. 2. Shell calls the kernel using a system call (execve). 3. Kernel prepares the process — allocates memory, loads the program from disk. 4. CPU executes instructions — reads the file, processes it. 5. Kernel handles I/O — fetches file data from disk into memory. 6. Output returns to shell — finally displayed on your terminal. Flow in short: User → Shell → Kernel → CPU → Memory & Disk → Kernel → Shell → User 🍽️ Easy Analogy — Restaurant CPU → The cook 👨🍳 Kernel → The manager 👩💼 Memory → Workspace 🍳 Disks/Devices → Storage & tools 🥘 OS + You → Restaurant & customer 🍽️ Without the manager, the cook wouldn’t know what to do. Without the cook, the manager’s plans are useless. Together, they make it all work. 💡 Takeaway Every command, click, or process in Linux flows through CPU, kernel, memory, and devices. Understanding this invisible teamwork makes Linux much clearer. #Linux #Kernel #CPU #MemoryManagement #OperatingSystem #OpenSource #TechLearning #LearningJourney #SoftwareEngineering #HowComputersWork #TechBasics #ProgrammingTips #DevCommunity #ComputerScience #ITInfrastructure #CloudComputing #SystemProgramming #CodeNewbie #TechEducation