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This is only tangentially related to the security issue, but I found that disabling hyperthreading on a cluster of dual Xeons running Linux greatly improved performance with a distributed memory (MPI) numerical model. Short summary: even if you only run your model on physical CPUs, hyperthreading will apparently bounce jobs around in a somewhat random way. Not sure if it's a hardware issue or a software (Linux) issue.

Here is a link which goes into detail

that is why raindrops have that famous teardrop shape

NO! Large falling raindrops do not have a teardrop shape - they are flattened with the major axis roughly parallel with the ground - shaped more like a hamburger bun before they break apart. Friction with the air causes the drop to distort as you indicate and high pressure is found below the drop, low above it.

I have a redergarden (not quite a renderfarm ;) and I've used POV-Ray to make visualizations and animations of my supercell model data. See the Novermber 2004 Linux Journal (cover plus article) for what I did. What I did was get POV-Ray, which, note, is "free" (with restrictions especially on the latest version) and got it to recognize my model data format natively (using the source of course). Then I can fire up my 14 of my nodes, all NFS mounted to a terabyte RAID array, with a python script (using pyMPI) and they each read in their data and happily render frames. Then I make movies with the resulting PPM images using mjpegtools.

Note that this approach crashes and burns if you can't fit the 3D array of your data into core memory. This becomes an issue especially with very large datasets and if you are rendering lots of different isosurfaces at once, which I often do. You can always downsample, or just read in what the camera sees instead of the whole model domain, but you can still run into brick walls with very large data sets. Of course, if you are rendering to a 1024x768 screen, and you are looking at the entire domain which is 700x700x100 you probably can downsample significanly without losing visual detail.

Anyway, for those interested, Here is a link to a directory conttaing mpegs and a talk I gave earlier this year which contains 1024x768 mpeg files and the talk itself. NOTE: some of these files are BIG. I would recommend this 32 MB mpeg and this 73 MB mpeg for a sample of what can be done with open source tools. Some supplemental material to the LJ article can be found here

Leigh Orf
Professor of Atmospheric Sciences
Central Michigan University

I have a redergarden (not quite a renderfarm ;) and I've used POV-Ray to make visualizations and animations of my supercell model data. See the Novermber 2004 Linux Journal (cover plus article) for what I did. What I did was get POV-Ray, which, note, is "free" (with restrictions especially on the latest version) and got it to recognize my model data format natively (using the source of course). Then I can fire up my 14 of my nodes, all NFS mounted to a terabyte RAID array, with a python script (using pyMPI) and they each read in their data and happily render frames. Then I make movies with the resulting PPM images using mjpegtools.

Note that this approach crashes and burns if you can't fit the 3D array of your data into core memory. This becomes an issue especially with very large datasets and if you are rendering lots of different isosurfaces at once, which I often do. You can always downsample, or just read in what the camera sees instead of the whole model domain, but you can still run into brick walls with very large data sets. Of course, if you are rendering to a 1024x768 screen, and you are looking at the entire domain which is 700x700x100 you probably can downsample significanly without losing visual detail.

Anyway, for those interested, Here is a link to a directory conttaing mpegs and a talk I gave earlier this year which contains 1024x768 mpeg files and the talk itself. NOTE: some of these files are BIG. I would recommend this 32 MB mpeg and this 73 MB mpeg for a sample of what can be done with open source tools. Some supplemental material to the LJ article can be found here

Leigh Orf
Professor of Atmospheric Sciences
Central Michigan University

I have a redergarden (not quite a renderfarm ;) and I've used POV-Ray to make visualizations and animations of my supercell model data. See the Novermber 2004 Linux Journal (cover plus article) for what I did. What I did was get POV-Ray, which, note, is "free" (with restrictions especially on the latest version) and got it to recognize my model data format natively (using the source of course). Then I can fire up my 14 of my nodes, all NFS mounted to a terabyte RAID array, with a python script (using pyMPI) and they each read in their data and happily render frames. Then I make movies with the resulting PPM images using mjpegtools.

Note that this approach crashes and burns if you can't fit the 3D array of your data into core memory. This becomes an issue especially with very large datasets and if you are rendering lots of different isosurfaces at once, which I often do. You can always downsample, or just read in what the camera sees instead of the whole model domain, but you can still run into brick walls with very large data sets. Of course, if you are rendering to a 1024x768 screen, and you are looking at the entire domain which is 700x700x100 you probably can downsample significanly without losing visual detail.

Anyway, for those interested, Here is a link to a directory conttaing mpegs and a talk I gave earlier this year which contains 1024x768 mpeg files and the talk itself. NOTE: some of these files are BIG. I would recommend this 32 MB mpeg and this 73 MB mpeg for a sample of what can be done with open source tools. Some supplemental material to the LJ article can be found here

Leigh Orf
Professor of Atmospheric Sciences
Central Michigan University

I have a redergarden (not quite a renderfarm ;) and I've used POV-Ray to make visualizations and animations of my supercell model data. See the Novermber 2004 Linux Journal (cover plus article) for what I did. What I did was get POV-Ray, which, note, is "free" (with restrictions especially on the latest version) and got it to recognize my model data format natively (using the source of course). Then I can fire up my 14 of my nodes, all NFS mounted to a terabyte RAID array, with a python script (using pyMPI) and they each read in their data and happily render frames. Then I make movies with the resulting PPM images using mjpegtools.

Note that this approach crashes and burns if you can't fit the 3D array of your data into core memory. This becomes an issue especially with very large datasets and if you are rendering lots of different isosurfaces at once, which I often do. You can always downsample, or just read in what the camera sees instead of the whole model domain, but you can still run into brick walls with very large data sets. Of course, if you are rendering to a 1024x768 screen, and you are looking at the entire domain which is 700x700x100 you probably can downsample significanly without losing visual detail.

Anyway, for those interested, Here is a link to a directory conttaing mpegs and a talk I gave earlier this year which contains 1024x768 mpeg files and the talk itself. NOTE: some of these files are BIG. I would recommend this 32 MB mpeg and this 73 MB mpeg for a sample of what can be done with open source tools. Some supplemental material to the LJ article can be found here

Leigh Orf
Professor of Atmospheric Sciences
Central Michigan University

I'm modeling supercells that produce tornadoes (well, almost) using supercomputers... does that count?

A talk I just gave a few days ago on this is found at the below link. Both in OpenOffice and PPT format. Note: the mpegs in that directory are BIG (1024x768) but they are very cool animations of supercells (raytraced with POV-Ray) and tornado-like circulations.

http://research.orf.cx/uw2004

Leigh Orf