MARC-Mälardalen University Automation Research Center’s Post

December 2023, we delivered our first Raspberry PI project. We initially developed the code on the 3 and then migrated to the 4 when it arrived. It was a great learning experience, and I am being open and saying, "First PI project ever!" - we did it! Delivery was a testament to the adage, "Say, yes! Figure it out later or as you go," which can be an opportunity to get past your know how inhibitions or shortcomings. While I am an #8BIT die-hard, the irony is not lost that I leaped into the #32BIT #LINUX embedded universe and got something out the door - no, the BORG haven't assimilated me. Yet, that is. I did notice that the accessories for PIs can be tricky to get hold of, especially if you are looking for "industrialized" options. We have a product line opening up in this vane, as below. A #PI #IO Board, designed to fit into a #dinrail enclosure. This is the first iteration, so we are interested in your thoughts and suggestions. The 26 I/O are grouped as 13 Optically Isolated Inputs, and 13 Transistorized outputs. For more information, feel free to message me on LinkedIn or email me via contactus@haventechnik.com. This product will be added to our other automation solution offering shortly: https://lnkd.in/dXZfhQU5 #32BIT #raspberrypi #linux #automation

🌟 Exploring Lightweight Processes (LWPs) 🌟 Continuing our series on process management, let's dive into Lightweight Processes (LWPs), also known as threads! LWPs enable multitasking within computing systems, enhancing efficiency and performance. 💻💡 - Episode 3: https://lnkd.in/e6kwQrTP - Episode 2: https://lnkd.in/e2yiH5DH - Episode 1 : https://lnkd.in/es86Sx9v Follow my RSS feed for updates: www.atomicl.net/index.xml #Computing #Multitasking #LWPs #Threads

Docker is an essential tool for developers, and managing containers on a Raspberry Pi can be streamlined with Portainer. While Docker Desktop provides a GUI for Mac and Windows, Portainer offers an intuitive web-based interface for Raspberry Pi running Raspbian. It allows users to start, stop, modify, or remove containers and monitor usage statistics efficiently. Running in its own container, Portainer is well-suited for single-board computers like the Raspberry Pi. Setting it up involves pulling the Portainer image and running a simple Docker command, after which it can be accessed via http://localhost:9000.

RPI Pico – Target: DIY and Education – Mistakes The biggest mistake of RPI Pico is CMAKE, used for a handful of ARM code,   which leads to complex IDE integration... and wasted time.   - Example: #STM32 & #Microchip, the most used MCUs – they don’t even have builder automation & system, just code in a few folders. They can be easily integrated anywhere.   - Second example: #PlatformIO / #Arduino for ESP32 also failed due to the complex binding with CMAKE, which created other misunderstandings.   - Third example: #NuttX and others, which are much more complex than Pico SDK – they use MAKE ... for many MCUs and boards ! Second is the structuring of the SDK source code – folder/file... folder/file (for a handful of code),   which results in total chaos and complex assembly documentation that is still missing to this day.   The tools also include ones that have no place there. Third – constant compiling of tools and the lack of precompiled ones – a waste of time. Fourth – to work effectively, you need Linux, which limits users on Windows, who statistically make up the majority.  This issue stems from the above points. Fifth – mixing the SDK and poorly thought-out ecosystem adds additional problems. Sixth – the arrogant attitude of RPI towards the Embedded (software) Community. And so on...  According to them, that's the "right" way. But if the target is #DIY and education The question is: Who exactly are they educating? The grown-up kids?

🌐 Exploring Device Drivers: Unveiling the Heartbeat of Hardware 🚀 ✨ Hey LinkedIn Fam! Dive into the intricate world of device drivers with my latest article, where we unravel the magic behind these unsung heroes bridging the gap between software and hardware. 🕹️🖥️ 🧭 Journey into the Article: We start with the basics - what are device drivers? Why do we need them? Explore the diverse types, from character and block drivers to network and graphics drivers, each playing a unique role in our computing experience. 🚀 Implementation Showcase: Ever wondered how a GPIO device driver for the Raspberry Pi looks in action? Check out the example code, complete with explanations, as we traverse the Linux kernel module terrain. Practical, hands-on learning at its finest! 💻🛠️ 🌟 Key Takeaways: - Understanding Types: Dive into character, block, network, filesystem, and graphics drivers. - Code Exploration: Unpack a simple GPIO device driver for the Raspberry Pi. - Importance: Discover the pivotal role of device drivers in ensuring system stability, flexibility, and security. 📊 Let's Get Interactive: 🤔 Question Time: What's your favorite type of device driver, and why? Drop your thoughts in the comments below and let's spark a discussion! 💬 🛠️ Hands-On: Try implementing a basic device driver for a peripheral you find fascinating. Share your experiences and challenges – we're all in this tech journey together! 👩💻👨💻 🔗 Link to the Full Article: https://lnkd.in/gTfPYuQM Let's keep the conversation buzzing! 🐝💼 Don't forget to like, share, and let me know your thoughts on this deep dive into device drivers. Here's to embracing the tech wonders that make our digital world spin! 🌐✨ #DeviceDrivers #TechExploration #LinuxKernel #CodingJourney #linux

#mdpienergies #highlycitedpaper Evaluation of Numerical Methods for Predicting the Energy Performance of Windows 👉 https://brnw.ch/21wLavK #heattransfer #mathematicalmodelling #windows #windowthermalresistance #thermaltransmittance

As an embedded engineer, I always wonder to connect the dots to understand the working of hardware resources at high scale applications like cloud containers. This post gave me a glimpse

If one container hogs too much of the CPU's resources, it can disrupt other programs running on the same machine. Netflix faced this problem and here’s how they solved it: The traditional way to manage this problem is through the operating system's task scheduler, like Linux's CFS. It divides CPU time fairly among programs. But with Netflix, they run millions of containers every month, serving various purposes from critical services to batch jobs. They needed better performance isolation. They decided to improve CPU isolation by moving away from relying solely on the operating system's scheduler. Instead, they used combinatorial optimization and machine learning. 𝗛𝗼𝘄 𝗜𝘁 𝗪𝗼𝗿𝗸𝘀: Instead of CFS's frequent interventions, they opted for a less frequent approach (every few seconds) and made better decisions based on actual usage data. For example, if one container is going to use a lot of CPU soon, they might place it on a different part of the hardware to minimize disruption to other containers. They used combinatorial optimization to efficiently solve the problem of allocating CPU resources to containers. They considered factors like cache usage and CPU needs. They implemented this strategy using Linux cgroups, which control resource allocation for containers. They had a system called titus-isolate that managed container placement based on predictions of future CPU usage. The system led to significant improvements, reducing the variance in job runtimes and improving predictability. For services, there was a notable capacity reduction needed to serve the same load with the required latency Service Level Agreement (SLA), along with reduced CPU usage on machines. I write one post for software engineers everyday at 10. Follow Pratik Daga so that you don't miss them.

🎉 Big news from Altair! The latest release of Altair HyperWorks (2023.1) brings support for Rocky Linux 8.4. This collaboration allows Altair customers to leverage HyperWorks solvers on Rocky Linux, backed by Altair's renowned enterprise-grade support. Discover the benefits of this integration here. https://bit.ly/3ULUxA7 #CIQ #altairpartner #RockyLinux 

After 20 Years in the Making: Real-Time Linux is Finally Here! This is huge! After two decades of hard work, debates, and setbacks, Real-Time Linux (PREEMPT_RT) has finally made its way into the mainline kernel, thanks to Linus Torvalds himself blessing the code at Open Source Summit Europe. Why does this matter? Real-Time Linux is not just about speed—it’s about reliability. Imagine a system where every microsecond counts—like in medical devices, industrial robots, or even space tech. Real-Time Linux is now set to power these mission-critical systems with precision timing, making sure tasks are done exactly when needed. The Journey Wasn't Easy: - Years of Challenges: It took 20 years of code rewrites, technical hurdles, and constant back-and-forth to get here. Steven Rostedt, a leading developer, said, "We rewrote things at least three times before they made it in." And that’s just a small glimpse into the countless hours poured into this project. - The Printk Problem: One of the biggest roadblocks was dealing with the printk function, a critical debugging tool in the kernel but a nightmare for real-time performance. Linus, who wrote the original printk code, was protective of it. After years of heated debates and several rejected proposals, a compromise was finally reached. Why This Matters Now: With Real-Time Linux baked into the upcoming Linux 6.12 kernel, we’re opening up a whole new world of possibilities. From smarter factories to next-gen healthcare, the impact will be felt across industries where timing and reliability are everything. Cheers to the future of Linux in real-time applications. Let’s see where this takes us! #Linux #RealTimeLinux #OpenSource #Innovation #TechNews