Hi Condor Users, I have a curious scheduling problem to solve and I hope an experienced user can help me out here. Thanks in Advance! COMPUTE INFRASTRUCTURE =========================== My compute infrastructure is made of many Racks. Each rack has a set of blades dedicated for computation. Currently, each rack is dedicated to a particular compute task. TASK NATURE ============= All compute tasks (on all racks) are MPI jobs. Not all racks are busy all the time and hence I am looking at a scheduler to scale my MPI jobs effectively. There is one more complication here. My MPI jobs are iterative. Each iteration runs not more than 2 seconds. CONDOR RELATED QUESTIONS ============================ 1. I just read Condor manual and have briefly experimented with it. My main problem is latency. If Condor takes even 1 second to reserve machines for my job, I have already lost my game. Can someone throw some light on what is the expected latency for reserving machines (assume 1 Gbps Ethernet network reserving for 20 machines) ? 2. If I model my individual MPI runs as DAGMan Jobs (to enforce dependency), then each Job will create a separate Cluster anyway and I will be in latency trouble. Alternatively, I could actually create a “Job Cluster” – which will execute my iterative MPI runs in a single cluster of nodes. This way I can hide my cluster creation latency. However, I don’t think I can dictate the dependencies within a Job Cluster using “DAGMan”. DAGMan only works at “Job Cluster” level. I don’t think it works at Process level inside a Cluster. How do I use Condor to solve this problem ? 3. I understand Condor provides Webservice APIs. Is there a way to request Condor to reserve some machines (based on a ClassAd) and block them for MPI runs and release them later on? 4. If Condor cannot solve this, Can you give a recommendation for an alternate scheduler? 5. Say, If I end up writing my own custom scheduler for this, Can anyone point out relevant technologies that will be useful? Thanks, Best Regards, KuruviNandan
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