Dell Vostro with Ubuntu: use the AMD Catalyst drivers

I have a Dell Vostro 3550 with Ubuntu 12.04 since around one year now.

The laptop worked fine, it was pretty fast, building a lot of projects in the same time, etc.

I complained with:

  • the temperature was really hot (sensors said between 80°C and 95°C all of the time). Sometime, the temperature was critical and the system shutted down.
  • due to the previous point, the fan was very noisy
  • the battery autonomy was average

This laptop use dual graphic cards: Intel SGI graphic card (to reduce energy consumption), and AMD Radeon HD 6600M (for 3D enhanced graphics and HD videos).

When I got this laptop, I tried to install the fglrx open source drivers a couple of times. Without success: it seems that the Radeon card was not fully supported.

As the laptop ran really fine (unity was fast, vlc was able to read HD videos without problem, etc), I stayed with the Intel Xorg driver.

Yesterday evening, watching a movie, the laptop was so hot that I have to use a pillow to avoid to burn my legs 😉

So today, I decided to find a solution.

As the fglrx open source drivers didn’t work, I try to proprietary AMD Catalyst drivers.

And now, ALL IS DIFFERENT 😉

The temperature stays around 70/80°C, so the fan are pretty quite, and the system is even faster than before.

More over, the admcccle (Catalyst Console) allows you to tweak the graphic card configuration. You can also choose and switch between the Intel SGI card or the RADEON one (it required a reboot).

To summarize, for all Dell Vostro users on Ubuntu (and more generally on Linux), install the ADM Catalyst graphics drivers 😉

Comments

Post a Comment

Popular posts from this blog

Exposing Apache Karaf configurations with Apache Arrow Flight

Image
This blog post shows how to use Apache Arrow and Arrow Flight in Apache Karaf runtime. The code base is available here: https://github.com/jbonofre/karaf-arrow . Apache Arrow ? Apache Arrow is composed by: The Arrow format (specification). Format implementations with different languages (C, Java, Go, Rust, ...). Extra subprojects like Flight, Flight SQL, ADBC, nanoarrow, ... Apache Arrow format is a in-memory columnar format, super efficient for scanning and iterating a large chunks of data. In traditional memory buffer, we focus on "row". Apache Arrow format "groups" data per column, which is much more efficient on modern CPUs/GPUs. The Apache Arrow format is basically a specification. We have several implementations for this specification: C C++ C# Go Java Python Ruby Rust As the purpose of this blog post is to show Apache Arrow in Apache Karaf, we will use Arrow Java. In addition, Apache Arrow also provides several...
Read more

Getting started with Apache Karaf Minho

Image
Apache Karaf Minho Apache Karaf Minho is a new runtime, completely created from scratch. The objectives are: super easy to use and run ligtning fast, including GraalVM support Kubernetes compliant to be easily used on the cloud helping to optimize cloud costs by supporting applications colocation providing turnkey services allowing you to create Minho applications in a minute Minho is composed by: minho-boot is the core of Minho. It contains the runtime launcher and the core services (service registry, lifecycle service, configuration service, ...). minho-* services provided additional functionnalities in the runtime. You can use these services to create your own services, it's also where you will find the services managing sepcific kind of applications, allowing colocation. minho-tooling optionally provide convenient tools to create your own runtime. It includes minho-maven-plugin for instance. In this blog post, we will take a quick tour on A...
Read more

Using Apache Karaf with Kubernetes

Image
In a previous blog post ( http://blog.nanthrax.net/?p=893 ), I introduced the “new” docker support in Karaf and the use of Karaf static distribution. This post follows the previous one by illustrating how to use Karaf docker image with a Kubernetes cluster. Preparing Karaf static docker image As in the previous blog post, we are preparing a Karaf static distribution based docker image. For this blog post, I’m using the example provided in Karaf: https://github.com/apache/karaf/tree/master/examples/karaf-docker-example/karaf-docker-example-static-dist . I’m just building the distribution as usual: karaf-docker-example-static-dist$ mvn clean install Preparing kubernetes testing cluster For this blog, I’m using a minikube installed locally. The installation is pretty simple: Download minikube from https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 Rename minikube-linux-amd64 as minikube Copy minikube in your path, for instance /us...
Read more