Although this list seems to have been quiet recently, perhaps there are some folks out there with wisdom to share. I didn't turn up much in the archives.
The group I am in is about to purchase a cluster. If anyone on this list has any advice on what type of hardware (or software) would be best, I'd appreciate it. We will have two broad types of uses: simulation studies for epidemiology (with people or cases as the units) and genetic and protein studies, with which I am less familiar. The simulation studies are likely to make heavy use of R. I suspect that the two uses have much different characteristics, e.g., in terms of the size of the datasets to manipulate and the best tradeoffs outlined below. Other uses are possible. Among other issues we are wondering about: *Tradeoffs between CPU speed, memory, internode communication speed, disk size, and disk speed. As a first cut, I expect the simulations suggest emphasizing processor power and ensuring adequate memory. On the other hand, the fact that it's easy to upgrade CPUs suggests putting more money into the network supporting the CPUs. And I suspect the genomics emphasizes more the ability to move large amounts of data around quickly (across network and to disk). *Appropriate disk architecture (e.g., local disks vs shared netword disks or SANS). 32 vs 64 bit; Intel vs AMD. We assume it will be some kind of Linux OS (we like Debian, but vendors tend to supply RH and Debian lacks support for 64 bit AMD in any official way, unlike Suse or RH). If there's a good reason, we could use something else. Our budget is relatively modest, enough perhaps for 10-15 dual-processor nodes. We hope to expand later. As a side issue, more a personal curiosity, why do clusters all seem to be built on dual-processor nodes? Why not more CPU's per node? Thanks for any help you can offer. -- Ross Boylan wk: (415) 502-4031 530 Parnassus Avenue (Library) rm 115-4 [EMAIL PROTECTED] Dept of Epidemiology and Biostatistics fax: (415) 476-9856 University of California, San Francisco San Francisco, CA 94143-0840 hm: (415) 550-1062 -- To UNSUBSCRIBE, email to [EMAIL PROTECTED] with a subject of "unsubscribe". Trouble? Contact [EMAIL PROTECTED]
