Bookmarks for April 14, 2009

admin — Tue, 28 Apr 2009 21:05:58 +0000

Links for April 14, 2009:

Lustre Wiki Main Page – "For the world's largest and most complex computing environments, the Lustre™ file system redefines high performance, scaling to tens of thousands of nodes and petabytes of storage with groundbreaking I/O and metadata throughput."
Virtual Proteomics Data Analysis Cluster | proteomics.mcw.edu – "ViPDAC uses Amazon Web Services to analyze proteomics data… ViPDAC [runs] on one of Amazon’s servers from where you can now access the ViPDAC web interface. At this point normal proteomics analysis procedures take over – you can pick an existing set of parameters or configure a new analysis (cleavage enzyme, modifications, protein database to search, etc) and select your data file (spectra in .mgf format) and then submit the job. ViPDAC will then upload the data file to the your area on Amazon’s S3 storage and run the analysis using the EC2 nodes available in your cluster. Once the analysis is complete ViPDAC will compile the results and save them back onto S3 where they can be stored or downloaded to the desktop for further analysis. At this point you can continue to do more analyses or simply turn the cluster off until you need it again."

Bookmarks for February 13, 2009

admin — Sun, 15 Feb 2009 15:29:39 +0000

Links for February 13, 2009:

Above the Clouds: A Berkeley View of Cloud Computing – “Cloud Computing, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service and shaping the way IT hardware is designed and purchased. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about overprovisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or underprovisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get results as quickly as their programs can scale, since using 1000 servers for one hour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT.”