Today , Dr. Frank Ham from Center for Turbulence Research, Stanford University attended a seminar in Uppsala University and gave a lecture on "Large Eddy Simulation on Unstructured Grids" . You can find the abstract of it here .
There is no doubt at all, that Computational Fluid Dynamics (CFD) is one the most complicated science that we have ever made ! And maybe that's why many of the most brilliant minds are working in this or related fields .
I was interested in two aspect of this lecture : the Visualization stage and the backbone GRID infrastructure of the their project .
Surprisingly , they need the technology 100 times faster than what they have now (Nov 2009) by the end of 2017 !! It means an enormous progress in both hardware and software . Can they achieve this ?? I don't know , but I hope so ....
Thursday, November 12, 2009
Monday, November 09, 2009
The second period
For the second period , I chose two courses :
"Scientific Visualization" and "Computer-intensive Statistics and Data Mining".
In Scientific Visualization course, they focus on VTK library and consider this huge library as a high level abstract one . I mean they don't concentrate on "under the hood" computer graphics basis; instead, they train students how to think from a level upper to determine the problem specifications and apply visualization techniques to demonstrate the results.
Another point about the course is that the formal programming language for this course is Python !! Oh my goodness ! It was one of the best news I had ever heard :)
But the second course is more interesting ; it's about "Statistical Pattern Recognition" ; thought, the primitive 8 lecture (out of 21 lectures) is about "random number generation, Monte Carlo , and Bootstrap techniques" . A nice point about this course is that We have to do our project in "R programming language" , which is an amazing language with exceptional capabilities for Statistical Programming .
Nevertheless , I have to try hard to dominate all of them . It takes 99% perspiration :)
"Scientific Visualization" and "Computer-intensive Statistics and Data Mining".
In Scientific Visualization course, they focus on VTK library and consider this huge library as a high level abstract one . I mean they don't concentrate on "under the hood" computer graphics basis; instead, they train students how to think from a level upper to determine the problem specifications and apply visualization techniques to demonstrate the results.
Another point about the course is that the formal programming language for this course is Python !! Oh my goodness ! It was one of the best news I had ever heard :)
But the second course is more interesting ; it's about "Statistical Pattern Recognition" ; thought, the primitive 8 lecture (out of 21 lectures) is about "random number generation, Monte Carlo , and Bootstrap techniques" . A nice point about this course is that We have to do our project in "R programming language" , which is an amazing language with exceptional capabilities for Statistical Programming .
Nevertheless , I have to try hard to dominate all of them . It takes 99% perspiration :)
Subscribe to:
Posts (Atom)