Quickly and Nicely Compress Your JPG

Just on my holidays and wanted to compress my JPGs under Linux to put them on Dropbox. Google really didn't yield anything quick 'n' dirty so I adopted the following:

mogrify -quality 75 *.jpg 

Clearly you can modify the quality parameter to your choosing. You can simply navigate to the directory containing images, run that command that will convert all your JPGs to a lower quality (remember to back them up first). 

Mogrify function is part of the ImageMagick kit so you might need to install that if that command is not found.

Where have you gone?

I'm sure many of you are hanging on tenterhooks for my next blog post. To be brief, I have just graduated and am taking a (well earned?) break. Have been travelling around Eastern Europe by train and now currently in the south of Spain.

Therefore, I haven't had much of a chance to keep up on news though someone did send me this which was definitely pretty big news and interesting comparison. It's a comparison of video transcoding using the two services. Amazon wins but I think it's pretty likely the gap will narrow shortly. Google to compete with Amazon's EC2 is big!...see my previous post for a look at the Amazon GPU infrastructure. When I get the time I will perform a comparison with the Google GPU infrastructure if it ever becomes available.

Getting Started with A GPU Cluster Instance On AWS

I recently received some free credit for Amazon Web Services (AWS) so I thought I may as well try it out! AWS is an absolutely incredible resource at a ridiculously low price. More specifically, I mean EC2 (Elastic Compute Cloud) The stats that Amazon come out with about it are insane, for example this snippet from the HPC page:
...a 1064 instance (17024 cores) cluster of cc2.8xlarge instances was able to achieve 240.09 TeraFLOPS for the High Performance Linpack benchmark, placing the cluster at #42 in the November 2011 Top500 list.
Pretty impressive!

I decided that it would be interesting to have a play with the GPU instances that one can use on AWS EC2. With each of these you get 2xTesla M2050 GPUs for very good value for money (though relatively expensive compared to other instance types) at $2 per hour.

So, I created my instance using the wizard, most of this is click through common sense stuff. The only thing to be careful with is to select the correct AMI on the first page: chose the one with GPU in the title!
Then the rest is just a matter of clicking through the wizard and downloading your *.pem file for passwordless ssh login (you need to do chmod 400 file.pem  to the newly downloaded file to be able to use it):  
ssh -i file.pem ec2-user@server-ip

You can get your server IP from the EC2 management console interface under "Public DNS".

OK, so at this stage I'm logged into my GPU instance. The first thing I run is nvidia-smi whereby I am greeted with the following message:
NVIDIA: could not open the device file /dev/nvidiactl (No such file or directory).
Nvidia-smi has failed because it couldn't communicate with NVIDIA driver. Make sure that latest NVIDIA driver is installed and running.

Hmm, that's not very friendly!
After some digging, it turns out I had been using the wrong instance type! During my rapid clicking, I should have selected cg1.4xlarge rather than cc1.4xlarge in one of the dialogs:

Rookie error.
After that, everything seems to be running as normal. Now to run some code.

 

Compiling

So once we're logged in with nvidia-smi up and running it's time to start compiling some code. This requires a couple of things such as the headers and the libs!
After some scraping around, the CUDA headers and libs can be found here and here:

/opt/nvidia/cuda/include/ 

/opt/nvidia/cuda/lib64/

While the OpenCL headers and libs can be found here and here:

/opt/nvidia/cuda/include/CL/

/usr/lib64/

From there, it's plain sailing. The performance is as good as I've ever seen it (For example, I don't know if they are perhaps virtualising the GPUs across multiple users? It seems not.)

Happy GPGPUing!

Using Embedded Webcam on Sony VAIO VGN-SZ61MN

A non GPU related post for a change. Was having trouble using the embedded webcam in my VAIO laptop under Ubuntu. After a bit of googling I found this thread which then leads to this page.

This only works if you have a Ricoh webcam. You can find this out by running lsusb in the terminal and see if it emits any lines with the word "Ricoh" in. I have no idea why Ricoh and Sony are using non standard webcam APIs but that's another story.

In short, run the following and you will have your Ricoh camera running on your VAIO:

sudo add-apt-repository ppa:r5u87x-loader/ppa
sudo apt-get update
sudo apt-get install r5u87x
sudo /usr/share/r5u87x/r5u87x-download-firmware.sh 

Now I can finally get round to that skype video call. Cheers Linux.