SC2001 Bandwidth Challenge demo:
Bandwidth Greedy Grid-enabled Object Collection Analysis for Particle Physics
Julian Bunn, Ian Fisk, Koen Holtman, Harvey Newman, James Patton, Suresh
OverviewThis was a demo done on 12-15 November 2001 at Supercomputing 2001 in Denver. We demonstrated a client/server application that allows particle physicists to interactively analyse 105 GB of physics event data stored in two `tier 2 centers' that are part of a Virtual Data Grid system. The demo showed some key elements of the CMS Data Grid system that the CMS particle physics experiment is building, in collaboration with several Data Grid reseach projects like GriPhyN, PPDG, and the EU DataGrid.
With this demo we participated in the Supercomputing 2001 `bandwidth challenge' event. We achieved a peak throughput of 29.06 Mbyte/sec from our two tier 2 servers at Caltech and SDSC into the client machine at the Denver show floor.
Bandwidth usage in the demo
Hardware usedWe used two servers at Caltech (Pasadena, CA) and UCSD (San Diego, CA). The two servers are shown below.
The Caltech server
The USCD server
Details about the Caltech server are here. The Caltech server had two 100 BaseT connections to a local router, and from there to the CalREN and Abilene networks. The UCSD server had one 100 BaseT connection. Of the two server installations, only the RAID arrays and front-end server machines were used, not the computational nodes which take the majority of the rack space in the pictures above.
The client machine is a standard dual-Pentium III PC running Linux. It is equipped with 512MB memory, a Fast Ethernet connection to the SCINet routers on the Denver show floor, and three Ultra SCSI3 disks.
The client machine in the process of being set up in the Caltech CACR booth in Denver.
On the left is Suresh Singh of Caltech.
Software usedThe servers and the client machines were all running Linux. We used the Objectivity/DB object database system to store all physics data in terms of objects. The 105 GB of physics data was generated with the CMS production software, using the ORCA-defined object data model.
We used the Globus GSI FTP tools to move bulk data between client and servers. To allow for grid-secured client-server communications (without passwords in the clear) we used an extended GDMP server and the GSI security libraries from the Globus project.
To support interactive physics analysis using `tag' data stored on the client machine, we used a home-grown Java-based prototype physics analysis application. To support analysis and replication of the data on the servers, we used a home-grown C++-based prototype Grid application.
Data sets used
COJAC showing all tracks in a FULL event (white lines) inside the CMS detector.
Only parts of the CMS detector are visualised here.
Representation of the server and client datasets and caches, and the
dataflow arrangement between them, as shown on screen during the demo.
The two purple boxes on the left represent the FULL data volumes. The boxes with purple bargraphs
in the middle and on the right are the caches for the LARGE objects. The black boxes with yellow
plots show a history of the data rates into these caches.
The two windows of the tag browser running on the client machine.
In this picture, 497 events have been selected out of the 144,000 available ones
by a combination of the predicate `part5E > 200' and the use of a `rubber band' selection
in the scatterplot in the lower left corner. The `rubber band' is the yellow box.
Virtual Data Grid APIThe demo software implements a virtual data grid API, an API that is central to the CMS computing model and the GriPhyN project.
After some events and corresponding LARGE objects have been seleced with the above tag browser application, the client application does requests access to these LARGE objects by doing a call on the local Virtual Data Grid API. This is shown in the picture below. The grid software, which runs on both the client and the server machines, is responsible for obtaining local copies of the LARGE objects. The Grid software returns and iterator, which the application can use to access the objects and plot some information in them.
The virtual data grid API as implemented in the demo
Whether or not (some of) the requested objects exist locally is completely transparent to the client application. The grid software will compute and perform the minimal actions that are necessary to fulfill the request. If some of the requested objects are already cached locally, only the missing ones will be transported over the network.
The same set of LARGE objects is requested twice, but with
differences in the contents of the caches. The graph shows the bandwith to fulfill the requests.
At the start of the first request, all caches are empty. Between the first and second
request, the client cache contents are manually deleted, but the
server caches are left intact.
Network detailsSee the hardware details above for a description of the network intefaces on each of the machines. To transport the bulk data with GSIFTP, we used 6 parallel TCP/IP streams, 4 from the Caltech server and 2 from the San Diego server. We used `large windows' on all streams, for the Caltech to Denver streams we used a window size of 400 KB, computed with the formulae RTT * link bandwidth. The complete route from Caltech to the Denver client is shown below.
traceroute to tier2.cacr.caltech.edu (188.8.131.52), 30 hops max, 38 byte packets 1 B-rtr.R340.showfloor.sc2001.org (184.108.40.206) 0.320 ms 0.255 ms 0.189 ms 2 core-rtr-2-sw-rtr-4a.scinet.sc2001.org (220.127.116.11) 0.345 ms 73.582 ms 7.058 ms 3 18.104.22.168 (22.214.171.124) 0.246 ms 0.189 ms 0.175 ms 4 snva-dnvr.abilene.ucaid.edu (126.96.36.199) 24.813 ms 24.817 ms 24.785 ms 5 losa-snva.abilene.ucaid.edu (188.8.131.52) 32.242 ms 32.245 ms 32.218 ms 6 USC--abilene.ATM.calren2.net (184.108.40.206) 32.462 ms 32.547 ms 32.490 ms 7 ISI--USC.POS.calren2.net (220.127.116.11) 33.062 ms 32.959 ms 33.044 ms 8 UCLA--ISI.POS.calren2.net (18.104.22.168) 33.527 ms 33.462 ms 33.580 ms 9 JPL--UCLA.POS.calren2.net (22.214.171.124) 34.296 ms 34.083 ms 34.133 ms 10 CIT--JPL.POS.calren2.net (126.96.36.199) 35.649 ms 35.604 ms 35.762 ms 11 Caltech-CalREN.caltech.edu (188.8.131.52) 35.602 ms 35.907 ms 35.781 ms 12 CACR-rtr.ilan.caltech.edu (184.108.40.206) 34.738 ms 34.755 ms 34.840 ms 13 tier2.cacr.caltech.edu (220.127.116.11) 35.116 ms 34.536 ms 34.421 msThe picture below shows how the network connections used in the demo relate to the multi-tier structure of the entire planned CMS data grid system.
Data flow in the demo, related to the multi-tier structure of the entire
planned CMS data grid system.
More demo pictures
ConclusionsIn this demo we showed
Koen Holtman, 31 Dec 2001.