Turn Idle Devices Into Windows Extended Screens Using Sunshine, Moonlight, and Virtual-Display-Driver

Create virtual displays using Virtual-Display-Driver, combined with Sunshine streaming server and Moonlight client, to turn Android phones, tablets, and other idle devices into wireless extended screens for Windows computers. This tutorial provides detailed configuration steps for all three tools to achieve an efficient screen extension solution within the same local network.

Why You Should Avoid Directly Returning Err in Go

In Go, error handling is a core design philosophy. Through explicit error return values (the error type), developers must face potential problems head-on. However, many developers new to Go (and even experienced developers) often make a mistake: directly returning the original err. This seemingly simple behavior actually buries hidden dangers for code debugging and maintenance. Problems with Directly Returning err 1. Opaque Error Information When you directly return err in multi-layer nested function calls, upper-level callers may have no idea where the error originated:

Deploying Deepseek-R1 Distilled Model on Archlinux

Recently, Deepseek released the R1 model, which has been extremely popular online. Having some free time, I decided to deploy the 7b version to play around with it. Using ollama can simplify the deployment process. After installing ollama with yay -S ollama, start the service with sudo systemctl start ollama, then run the command ollama run deepseek-r1 to begin chatting. However, I quickly noticed something was wrong - why was the generation speed so slow? Checking the task manager, I found that inference was running on CPU without any GPU acceleration, so I started troubleshooting. Looking at the ollama service logs with journalctl -u ollama -f, I found a warning: no cuda runners detected, unable to run on cuda GPU, but I obviously have CUDA drivers installed. So I searched online extensively and was speechless when I found the solution. In the AUR repository, besides ollama, there’s also ollama-cuda - you need to install both to enable CUDA acceleration.

Archlinux Clevo Laptop Driver and Control Center Installation

The fan scheduling on Clevo computers is really annoyingly loud. I used to use Windows and relied on Ryzen Master for undervolting to control CPU temperature, which indirectly reduced fan speed. Now that I’ve switched to Linux, it’s unbearable without proper configuration. I spent ages searching on Google and found a bunch of GitHub repositories. After trying several that didn’t work well, I finally discovered that someone in the AUR repository had already packaged useful solutions (I absolutely love pacman and AUR!). https://aur.archlinux.org/packages?K=clevo
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