Affinity scheduling of processes on symmetric multiprocessing sy

Details Affinity scheduling of processes on symmetric multiprocessing sy Affinity scheduling of processes on symmetric multiprocessing sy

1994-03-24

1996-04-09

Kriess, Kevin A.

Boots, shoes, and leggings

364DIG1, 3642813, 364280, 3642421, 3642818, G06F 946

Patent

active

055069878

ABSTRACT:
A method of scheduling processes on a symmetric multiprocessing system that maintains process-to-CPU affinity without introducing excessive idle time is disclosed. When a new process is assigned, the process is identified as young and small, given a migtick value and assigned to a specific CPU. If the priority of a process placed on a run queue is above a threshold, the high priority count of the assigned CPU is incremented. At predetermined clock intervals, an interrupt occurs that causes the migtick value of running processes to be decremented. Then each CPU is tested to determine if its high priority count is greater than zero. CPUs having high priority counts greater than zero are tested to determine if any processes having a priority greater than the priority of the running process are assigned. If higher priority processes are assigned to a CPU having assigned processes lying above the threshold, a context switch takes place that results in the higher priority process being run. At regular intervals, a migration deamon is run to load balance the multiprocessor system. First, a large/small process threshold is determined. Then processes whose migtick values are below a migtick threshold (e.g., 0) are identified as old. Old processes then are identified as large or small processes based on their memory usage. Next, a determination is made of whether the small and large process load balances of the system can be improved. If either or both can be improved, the smallest small and/or the smallest large processes are migrated from their assigned CPU to the CPU with, as the case may be, the least large or the least small processes.

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"The Influence of Workload on Load Balancing Strategies" by Luis-Felipe Cabrera, IBM Res. Ctr., California.
Luis-Felipe Cabrera, "The Influence of Workload on Load Balancing Strategies," IBM Almaden Research Center, San Jose, California.
Derek L. Eager, Edward D. Lazowska and John Zahorjan, "Adaptive Load Sharing in Homogeneous Distributed Systems," IEEE Transactions on Software Engineering, vol. SE-12, No. 5, May 1986.

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