An improved replacement strategy for function caching
LFP '88 Proceedings of the 1988 ACM conference on LISP and functional programming
Incremental computation via function caching
POPL '89 Proceedings of the 16th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
GTW: a time warp system for shared memory multiprocessors
WSC '94 Proceedings of the 26th conference on Winter simulation
Caching intermediate results for program improvement
PEPM '95 Proceedings of the 1995 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation
Adaptive functional programming
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Updateable simulation of communication networks
Proceedings of the sixteenth workshop on Parallel and distributed simulation
Dynamic Programming
Transparent and adaptive computation-block caching for agent-based simulation on a PDES core
Proceedings of the 40th Conference on Winter Simulation
Efficient Master/Worker Parallel Discrete Event Simulation
PADS '09 Proceedings of the 2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation
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We investigate factors affecting the performance of caching to speed up discrete event simulation. Walsh and Sirer have shown that a variant of function caching (staged simulation) can improve the performance of simulation in a networking application. However, the effectiveness of caching depends significantly on cache size, the cost of consulting the cache, the hit rate, and the cost of completing the computation in case of a cache miss. We hypothesize that adaptive techniques can be used to optimize caching parameters and demonstrate an adaptive scheme that decides whether to utilize caching depending on observed cache performance and event processing times. We focus on evaluating quantitative relationships, using our own caching implementation with the P-Hold synthetic workload application running on the GTW simulation kernel. Experiments show that as the cache size is increased, performance improves to a point, then degrades, and also that the adaptive technique can substantially improve speedup.