{"id":"topology-job-admission","level":"infrastructure","name":"Job admission, topology and resource fragmentation","shortName":"Job admission, topology and resource fragmentation","role":"Places complete jobs onto compatible resources while balancing utilization and service goals.","description":"A distributed job needs a compatible set of devices, enough local memory and the connections required by its partitioning. Having many free devices across a cluster does not guarantee that a sufficiently connected group is available. A scheduler considers resource requests, placement, reservations and policy; Slurm’s topology guide shows how connectivity can inform selection. The broad concept of admitting a parallel job together is distinct from Slurm’s particular time-sliced gang-scheduling feature. Fragmentation, priority and reserved headroom can all leave physically healthy hardware temporarily idle. Useful scheduling therefore balances job completion and service targets rather than maximizing a single occupancy number.","specs":[{"label":"Resource request","value":"Devices, memory, topology and duration","context":"A count alone omits important compatibility constraints."},{"label":"Utilization versus goodput","value":"Busy resources versus useful accepted work","context":"Unproductive retries or deadline misses can inflate activity."}],"interfaces":[{"name":"Queued jobs and policy","direction":"in","signal":"Required resources, priorities and placement constraints"},{"name":"Admitted allocation","direction":"out","signal":"A compatible job resource set and execution start"}],"tradeoff":"Tight placement can improve communication while increasing queue wait; backfilling smaller jobs uses gaps but must respect promised reservations.","whyAI":"Model shards that fit individually can still wait because their group cannot be placed on a suitable topology.","related":["scheduler","parallelism","scaleup-scaleout-boundaries"],"sources":[{"title":"Slurm Topology Guide","url":"https://slurm.schedmd.com/topology.html"}],"scale":"Job allocation across nodes, storage tiers and recovery time","kind":"architecture","branch":"Data-center operations","subbranch":"Scheduling, storage and retained work","mechanism":["Specify each job’s complete resource and communication requirements.","Identify healthy free resources with compatible memory and software configurations.","Evaluate whether the required connected group exists under current reservations.","Choose admission and placement according to explicit completion-time or latency objectives.","Measure wait time, fragmentation and useful progress before changing scheduling policy."],"misconception":"An idle device is not always wasted capacity; it may be an unusable fragment or reserved headroom for a defined service target.","check":{"question":"Why can an eight-device job wait while eight devices are free?","options":["The scheduler cannot count beyond seven","The free devices may not form a compatible required topology","Device counts automatically guarantee placement"],"answer":1,"explanation":"Memory, software and connectivity constraints can prevent a collection of free devices from forming a valid allocation."},"science":[{"title":"Allocation feasibility","equation":"Feasible(job) = count ∧ memory ∧ compatibility ∧ topology ∧ policy","explanation":"Each term is a Boolean constraint for the requested allocation.","assumptions":"A pedagogical constraint model; real schedulers also handle failures, priorities, time and implementation-specific resources."}],"prerequisites":["scheduler","parallelism"],"learningObjective":"Explain resource fragmentation and distinguish policy from physical capacity.","workstream":"W09","visualFamily":"hall-system","engineeringExample":"Synthetic cluster has four free devices in each of two slow-linked domains. An eight-device job requiring one local domain waits, while two independent four-device jobs may fit immediately.","evidenceNotes":"No real user queue or reservation is inferred. Slurm’s named gang-scheduling implementation is not conflated with generic simultaneous parallel-job admission.","labId":"engineering","scope":"Propagate a stated facility power budget, PUE, readiness and utilization to illustrative work; detailed conversion, battery, cooling and grid models are not included.","deepLabId":"hall","investigationId":"manufacturing","labScope":"Propagate a stated facility power budget, PUE, readiness and utilization to illustrative work; detailed conversion, battery, cooling and grid models are not included."}