disCERNing Data Analysis
technodummy writes: "Wired is reporting how CERN is driving the Linux-based, EU funded, DataGRID project. And no, they say, it's nothing like Seti@Home. The description on the site of the project is: '
The objective is to enable next generation scientific exploration which requires intensive computation and analysis of shared large-scale databases, from hundreds of TeraBytes to PetaBytes, across widely distributed scientific communities.'" If you're interested in this, check out the Fermi Lab work with LinuxNetworkX data as well as the all-powerful Google search on the Fermi Collider Linux project. As jamie points out, "Colliders produce *amazing* amounts of data in *amazingly* short time periods... on the order of "here's a gigabyte, you have 10 milliseconds to pull whatever's valuable out of it before the next gigabyte arrives".
here's a gigabyte, you have 10 milliseconds to pull whatever's valuable out of it before the next gigabyte arrives.
let's see. 1 GB in 10 ms works out to 100 GB per second. how recently did GB ethernet come about? and what would the average bandwidth of users be? i would guess much less, but let us assume 100KB per second.
so you have 107374182400 bytes of data per second. your users can take 102400 bytes per second each. even if everyone was connected directly to your network (no delays or bottlenecks... ha!) you would still require 1048576 users (that is over 1 million).
and this is not taking into effect sending any data BACK to the source or actual computation time on the users.
-sam
burn the computers. go back to the abacus.
The WWW, developed at CERN by Tim Berners-Lee springs to mind..
The problem is that there's way too much data to write to any storage medium to analyze later. The bandwidth makes hard drives look like tiny, tiny straws. When they throw the switch and the protons or whatever start smacking into each other, they get many collisions in a row, several every millisecond, maybe dozens every millisecond (depending on collider circumference I imagine). The huge array of detectors around the collision point stream out big chunks of data for each collision. The first line of defense is a network of computers that get handed each collision, or parts of it broken down, in round-robin order or something. Their job is to sift through X megabytes very quickly to decide whether there's anything "interesting" in this collision that warrants being remembered. If no flags go up, the data just gets dropped on the floor.
The datagrid described in the article is, as far as I can tell, set up to process data after that "first line of defense" -- even after dropping the majority of the bits on the floor, there is still a prodigious amount that has to be sifted through, just to check that the Higgs didn't leave a track or something. That's a different sort of engineering project.
My point was just that, yes, the amount of data involved here really is amazingly large.
Has anyone actually seen an IT related EU project that achieved something?
Government funded work, in the EU, US and internationally, actually drive changes in the IT industry a lot more than most people realise (or perhaps would care to admit).
For christssakes, the web itself came out of a CERN project! Also many other web standards originated in EU funded projects, for instance JPEG and MPEG. So, the most common formats on the web for text (HTML), images (JPEG), and video (MPEG), all owe something to funding from the EU.
And of course the Internet itself comes from US government funded projects. Even commonly used business process have resulted from government funded work (project management methodologies).
Both Americans and Europeans like to bitch about the inefficies of their governments, but the fact of the matter is that if you look at the history of IT, more fundamental innovations come from government funded work than from industry. Of course Bill Gates, Larry Ellison etc. don't want you to think that, but that's the way it is.
or just write it all as it comes in and analyze it later.
1 GB per 10 ms comes out to 100 GB per second. after 24 hours of experimentation, you find yourself with 8.6 million gigabytes. hard drives are cheap, but not THAT cheap. and even if you had LOTS of 100 GB hard drives, you still need to find a place to PUT 86 thousand of them.
every 24 hours.
after 1 week's worth of data collection, you have 600 thousand 100 GB hard drives of data.
this is why 'store now, analyze later' is not as good of an option for collision data. you have to take that 100 GB of data per second, and first filter and say, 'which of these collisions might be interesting to look at? which ones produced the particles we are trying to study?'
-sam
burn the computers. go back to the abacus.
Actually the Fermilab article pointed to concerns a cluster of machines used for the L3 trigger of the D0 experiment (of which I'm a member). This actually has very little to do with the GRID since it is used as the final stage of a three stage trigger process which decides when an "interesting" event has been produced by the collider. The previous stage, L2, also uses Linux/Alpha machines but is not really a cluster since these custom built boards sit in various crates of electronics and process only a fraction of the data that the L3 sees (however our time budget at L2 is 100 microseconds compared to L3's 100 milliseconds!).
However, that said, D0 is heavily involved with the GRID project and has what is arguably one of the first production GRID applications, called SAM. This system essentially manages all of our data files around the entire globe and allows any member to run an analysis job on a selected set of data files. SAM then handles the task of getting those files to the machine where the job is running using whatever means is required (rcp or fetching it from a tape store). SAM also allows remote institutes to add data to the store which is used primarily by large farms of remote Linux boxes which run event simulations. We are also currently working on integrating SAM into our desktop Linux cluster which will allow us to use the incredibly cheap disk and CPU which is available for Linux machines. For more details you can consult the followng web pages:
http://www-d0.fnal.gov/ - the D0 homepage
http://d0db.fnal.gov/sam - the SAM homepage