VAX/VMS internals and data structures
VAX/VMS internals and data structures
SIGMETRICS '86/PERFORMANCE '86 Proceedings of the 1986 ACM SIGMETRICS joint international conference on Computer performance modelling, measurement and evaluation
Memory management and response time
Communications of the ACM
Dynamic space-sharing in computer systems
Communications of the ACM
The benchmarking, tuning and analytic modeling of VAX/VMS
SIGMETRICS '79 Proceedings of the 1979 ACM SIGMETRICS conference on Simulation, measurement and modeling of computer systems
Workload characterization and performance evaluation in a research environment
SIGMETRICS '82 Proceedings of the 1982 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Multiple class memory constrained queueing networks
SIGMETRICS '82 Proceedings of the 1982 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Fast approximate solution of multiprogramming models
SIGMETRICS '82 Proceedings of the 1982 ACM SIGMETRICS conference on Measurement and modeling of computer systems
IEEE Transactions on Software Engineering
Hi-index | 0.98 |
Digital Equipment Corporation's VAX/VMS operating system maintains a paging cache in memory consisting of modified, free, and shared pages. Pages in the cache are faulted to process resident sets without incurring disk I/O. Pages not in memory are stored on disk and cause a read or 'hard' fault, when referenced. When memory is constrained VMS favors global page reclamation from process resident sets, keeping those processes in memory with smaller resident sets rather than swapping them to disk. This sophisticated scheme to manage paged memory is represented by analytic single class and simulation multiple class models faithful to the details of VMS memory management. Workload dependent equations, developed empirically from experimental data, are used to predict page faults and the percent of which are resolved from disk. Both models were carefully validated against measurement data and predict accurately under different workloads and hardware configurations.