Hi Ross, Your "node pull" system sounds fast, stable and well suited for the workflow that you need to manage/operate. I certainly would not throw it away in favor of a more general purpose cluster queuing system like SGE if you go the dedicated resource route. You may want to plan on keeping your existing workflow system while also planning to deploy distributed resource management suite like Platform LSF or Sun Grid Engine on to the same hardware. There is no reason why your 'pull' system can not be used alongside a more general purpose resource allocation and scheduling framework. This lets you use 'what works' for your most important workflow while also providing a more general purpose framework for use perhaps by others in your institution. Providing a share NFS resource to the dedicated hardware will make the usage and management of the queuing system easier but it is not an absolute requirement for either SGE or LSF. Hardware selection is something I can't really help with -- you are in the position to make the most informed decision and seem to have the benchmarking process well in hand. If pressed I'd say that the most "common" hardware configuration I see is a dual-CPU box with 4GB of physical memory. There are plenty of exceptions though both in CPU count and memory size. The apps that you did mention are performance bound by both memory and disk IO speeds. You will probably find that you can get a significant speed boost by benchmarking on nodes that have 2 drives mirrored or striped via a software RAID set. The IO gains with multiple drives and software RAID can be significant. -Chris Ross Crowhurst wrote: > Also, our existing farm uses "node pull". That is, as nodes come online a process on each node requests from a mysql configuration database the type of jobs that the node is capable of undertaking, then requests a chunk of jobs from a mysql database functioning as a jobs queue. The nodes process their chunk of jobs and post parsed results directly back to the appropriate mysql database. All blasts are performed by piping from the control script to blast then piping results back in for parsing. No physical sequence/report files are read or written to local disk (except for interproscan). I used to use NFS and have the nodes send results files back to an NFS server where they were parsed to database but that is incredibly slow compared to the system I now operate. The "node pull" system seems ideal for our current environment but if we move to a farm/cluster that is available 24x7 there may be a better way to do it (use SGE, standard cluster queuing systems etc). If I move to splitting databases then its seems I am back to using NFS, generation of physical reports and parsing these on one or more servers (parsing itself could be a new job type and merged blast reports redistributed to the cluster to parse?). Is there a consensus on the best or most appropriate way to tackle this in a dedicated cluster environment? I would welcome input on this as well. -- Chris Dagdigian, <dag@sonsorol.org> BioTeam - Independent life science IT & informatics consulting Office: 617-665-6088, Mobile: 617-877-5498, Fax: 425-699-0193 PGP KeyID: 83D4310E iChat/AIM: bioteamdag Web: http://bioteam.net