Design and implementation of dynamic load balancing algorithms for rollback reduction in optimistic PDES
TLDR
Two algorithms for dynamic load balancing which reduce the number of rollbacks in an optimistic PDES system are proposed which are based on the load transfer mechanism between lps and the process migration which migrates logical processes between several pairs of physical processors.Abstract:
In an optimistic parallel simulation, logical processes (Ips) proceed with their
computation without any constraints. However, if the computing requirements of
different lps are not balanced or if the processors are not homogeneous, some lps may
lag behind in simulation time while others surge forward. In other words, if the
simulation clocks of different lps are not progressing at the same rate, cascading
rollbacks may occur nullifying the potential benefit of an optimistic parallel discrete
event simulation (PDES). Hence it is necessary to balance the computational load on
different lps in such a way that their local simulation clocks advance almost at the same
rate. In this paper, we propose two algorithms for dynamic load balancing which reduce
the number of rollbacks in an optimistic PDES system. Our first algorithm is based on
the load transfer mechanism between lps; while the second algorithm, based on the
principle of evolutionary strategy, migrates logical processes between several pairs of
physical processors. We have implemented both of these algorithms on a cluster of
heterogeneous workstations and studied their performance. The experimental results
show that the algorithm based on the load transfer is effective when the grain size is
greater than 10 milliseconds. The algorithm based on the process migration yields good
performance only for grain sizes of 20 milliseconds or larger. In both of these cases the
speed up ranges mostly between and 2 using four processors.read more
Citations
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Journal ArticleDOI
An adaptive partitioning algorithm for distributed discrete event simulation systems
TL;DR: The results obtained indicate clearly that a partitioning which make use of the simulated annealing significantly reduces the running time of a conservative simulation, and decreases the synchronization overhead of the simulation model when compared to Nandy-Louck's partitioning algorithm.
Proceedings ArticleDOI
A segment-aware multi-core scheduler for system C PDES
TL;DR: A dynamic load-profiling and segment-aware scheduling algorithm with optimized thread dispatching to maximize parallel SystemC simulation speed, which generally can be applied to all work-sharing PDES approaches.
Optimizing Many-Threads-to-Many-Cores Mapping in Parallel Electronic System Level Simulation
TL;DR: This dissertation proposes a computation- and communication-aware approach to optimize thread mapping for parallel ESL simulation, with the aims of load balancing and communication minimization, and shows a significant performance gain on top of the order-of-magnitude speedup of PDES.
References
More filters
Journal ArticleDOI
An adaptive partitioning algorithm for distributed discrete event simulation systems
TL;DR: The results obtained indicate clearly that a partitioning which make use of the simulated annealing significantly reduces the running time of a conservative simulation, and decreases the synchronization overhead of the simulation model when compared to Nandy-Louck's partitioning algorithm.
Proceedings ArticleDOI
A segment-aware multi-core scheduler for system C PDES
TL;DR: A dynamic load-profiling and segment-aware scheduling algorithm with optimized thread dispatching to maximize parallel SystemC simulation speed, which generally can be applied to all work-sharing PDES approaches.
Optimizing Many-Threads-to-Many-Cores Mapping in Parallel Electronic System Level Simulation
TL;DR: This dissertation proposes a computation- and communication-aware approach to optimize thread mapping for parallel ESL simulation, with the aims of load balancing and communication minimization, and shows a significant performance gain on top of the order-of-magnitude speedup of PDES.