new book list

I've come across so many books lately that I need to start compiling a book list. Not that I'll ever have time to read them all and reflect on them, but I should at least keep track of a list of books that I ought to read. What do you think?

New Project Idea

I had this dream the other night about writing an app. that does image and videos and networking, and I am beginning to shape an app. that is useful. Luckily, I found a partner who is also interested, and we are going to see if this works. All of a sudden I feel some life again.

parallel computing toolbox in matlab

Got my first program working using the parallel computing toolbox and saw some good speedups. Next, I will take the concept and apply it to images, and show that it also works. In images, I need to create distributed arrays, which is defined differently in matlab 2009b and 2009a. I'm not going to figure out how it works in 09a, and just work on the 09b version.

ICIP 2010 - Feb. 8

I thought the deadline for ICIP 2010 is today, but a quick look at the website, it's been extended for two weeks, which suggests that the economy in the research community hasn't completely recovered yet, and North American institutions are still struggling to find money to get students/prof to go oversea to Asia for a conference.

And this is also an opportunity for me to take advantage of the extension to work hard and get a chance to go back to my motherland.

GPU - future of computing

My prof thinks GPU will play a huge role in the future of computing, especially in image/video coding. Real-time encoding of video has always been an issue due to the complexity of the encoder, especially with H.264 being a much more sophisticated encoder than its predecessor. But with the advent of GPU processing, these encoder complexity will become lesser of an issue, assuming that one can achieve parallel programming at the encoder side.

I think the future of video coding must make use of parallel coding paradigm. Maybe the design of such codecs may not give you optimal performance, but it should be aware of what parallel computing can offer, and thus strike a balance between performance and complexity. After all, this is always the main tradeoff in computing, isn't it?

acm programming from SLPC

The Stanford Local Programming Contest page has a lot of goodies (resources) provided to its students, or everyone really. I went nuts last night downloading most of the problems.

http://cs.stanford.edu/group/acm/SLPC/

Of course the real key is to read the problems and think about them, and knowing that they provided solutions really helped because you can improve by comparing your solution and *the* solution.

I am thinking these problems can occupy my time during the times when I do my daily commute from point A to point B, as well as being physically at places where mentally I can be doing something else.

Introduction to Algorithms

I feel a bit ashamed that I'm starting to read this book now, when I should have been reading it 10 years ago. So when I found out that the 3rd edition came out not too long ago, I purchased the book out of impulse response. I guess when a book is regarded as a bible in the field, then it's ok to own it.

http://www.amazon.ca/Introduction-Algorithms-Third-Thomas-Cormen/dp/0262033844/ref=pd_sim_b_1