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Parallel task scheduling (also called parallel job scheduling [1] [2] or parallel processing scheduling [3]) is an optimization problem in computer science and operations research. It is a variant of optimal job scheduling .
Whenever a priority job arrives at the system, that job will be given priority with respect to all other jobs, even over the ones which are currently being executed on the processors. In this case, when a priority job arrives, the sub-gang which is currently executing on the system will be stopped and all the progress that has been made will be ...
Fractional job scheduling is a variant of optimal job scheduling in which it is allowed to break jobs into parts and process each part separately on the same or a different machine. Breaking jobs into parts may allow for improving the overall performance, for example, decreasing the makespan.
Jobs priority Group priority Queue type SMP aware Max exec node Max job submitted CPU scavenging Parallel job Job checkpointing Python interface Enduro/X: C/C++: OS Authentication GPG, AES-128, SHA1 None Any cluster Posix FS (gfs, gpfs, ocfs, etc.) Any cluster Posix FS (gfs, gpfs, ocfs, etc.) Heterogeneous OS Nice level OS Nice level SOA Queues ...
The model is often used for parallel computations [2] or systems where products need to be obtained simultaneously from different suppliers (in a warehouse or manufacturing setting). [ 3 ] : 78–80 The key quantity of interest in this model is usually the time taken to service a complete job.
HTCondor can run both sequential and parallel jobs. Sequential jobs can be run in several different "universes", including "vanilla" which provides the ability to run most "batch ready" programs, and "standard universe" in which the target application is re-linked with the HTCondor I/O library which provides for remote job I/O and job ...
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