Time Warp Parallel Simulation Research Articles

Throttled Lazy Cancellation in Time Warp Parallel Simulation

Time Warp parallel simulations need efficient schemes to cancel erroneous event messages in order to achieve acceptable performance levels. Lazy cancellation depends on delaying the cancellation of incorrect computations until rolled-back events are re-processed. An antimessage is then sent for cancellation only if an output message re-produced after rollback is found to be unequal to its counterpart produced before rollback. One drawback of this approach is that antimessages are sent too late to catch the wave of incorrect computations, which results in more rollbacks. In this paper, we suggest an enhanced lazy cancellation technique that aims to throttle incorrect computations. It asks logical processes (LPs) that have received any output messages, generated from the first execution of a rolled-back input event in some neighboring LP, to mark those messages as temporarily blocked. Those messages remain in a blocked state until it is later decided whether or not they must be cancelled. The receiving LP becomes blocked only after a blocked input message becomes the next message to process. After re-executing the rolled-back input event, the sending LP sends each of its receiving LPs either an `Unblock' message or an antimessage for each previously marked output message, depending on the result of the equality test of that output message's versions before and after rollback. Experimental results for a synthetic benchmark show that our technique can yield better performance than both lazy and aggressive cancellation.

A checkpointing–recovery scheme for Time Warp parallel simulation

This paper presents a checkpointing–recovery scheme for Time Warp parallel simulation. The scheme relies on a checkpointing protocol, namely mixed state saving, embedding both sparse and incremental state saving modes, and on a state recovery procedure embedding both forward and backward recovery modes. This scheme is a generalization of many previous solutions, which can be obtained as particular instances of it by selecting appropriate values for the checkpointing protocol parameters. We also present two regulating algorithms to adaptively tune the checkpointing protocol parameters, in order to make the protocol reacting to variable rollback behavior. A synthetic benchmark in several different configurations has been used for evaluating and comparing our scheme with previous solutions. The obtained data show that our solution allows faster execution and, in addition, keeps quite low the amount of memory used for recording state information; this allows the scheme to not adversely affect performance when memory is a critical resource.

A cost model for selecting checkpoint positions in time warp parallel simulation

Recent papers have shown that the performance of Time Warp simulators can be improved by appropriately selecting the positions of checkpoints, instead of taking them on a periodic basis. In this paper, we present a checkpointing technique in which the selection of the positions of checkpoints is based on a checkpointing-recovery cost model. Given the current state S, the model determines the convenience of recording S as a checkpoint before the next event is executed. This is done by taking into account the position of the last taken checkpoint, the granularity (i.e., the execution time) of intermediate events, and using an estimate of the probability that S will have to be restored due to rollback in the future of the execution. A synthetic benchmark in different configurations is used for evaluating and comparing this approach to classical periodic techniques. As a testing environment we used a cluster of PCs connected through a Myrinet switch coupled with a fast communication layer specifically designed to exploit the potential of this type of switch. The obtained results point out that our solution allows faster execution and, in some cases, exhibits the additional advantage that less memory is required for recording state vectors. This possibly contributes to further performance improvements when memory is a critical resource for the specific application. A performance study for the case of a cellular phone system simulation is finally reported to demonstrate the effectiveness of this solution for a real world application.

An adaptive memory management protocol for Time Warp parallel simulation

It is widely believed that Time Warp is prone to two potential problems: an excessive amount of wasted, rolled back computation resulting from “rollback thrashing” behaviors, and inefficient use of memory, leading to poor performance of virtual memory and/or multiprocessor cache systems. An adaptive mechanism is proposed based on the Cancelback memory management protocol that dynamically controls the amount of memory used in the simulation in order to maximize performance. The proposed mechanism is adaptive in the sense that it monitors the execution of the Time Warp program, automatically adjusts the amount of memory used to reduce Time Warp overheads (fossil collection, Cancelback, the amount of rolled back computation, etc.) to a manageable level. The mechanism is based on a model that characterizes the behavior of Time Warp programs in terms of the flow of memory buffers among different buffer pools. We demonstrate that an implementation of the adaptive mechanism on a Kendall Square Research KSR-1 multiprocessor is effective in automatically maximizing performance while minimizing memory utilization of Time Warp programs, even for dynamically changing simulation models.

Selecting the checkpoint interval in time warp simulation

In Time Warp parallel simulation, the state of each process must be saved (checkpointed) regularly in case a rollback is necessary. Although most existing Time Warp implementations checkpoint after every state transition, this is not necessary, and the checkpoint interval is in reality a tuning parameter of the simulation. Lin and Lazowska[6] proposed a model to derive the optimal checkpoint interval by assuming that the rollback behavior of Time Warp is not affected by the frequency of checkpointing. An experimental study conducted by Preiss et al.[10] indicates that the behavior of rollback is affected by the frequency of checkpointing in general, and that the Lin-Lazowska model may not reflect the real situations in general. This paper extends the Lin-Lazowska model to include the effect of the checkpoint interval on the rollback behavior. The relationship among the checkpoint interval, the rollback behavior, and the overhead associated with state saving and restoration is described. A checkpoint interval selection algorithm which quickly determines the optimal checkpoint interval during the execution of Time Warp simulation is proposed. Empirical results indicate that the algorithm converges quickly and always selects the optimal checkpoint interval.

Optimal memory management for time warp parallel simulation

Recently there has been a great deal of interest in performance evalution of parallel simulation. Most work is devoted to the time complexity and assumes that the amount of memory available for parallel simulation is unlimited. This paper studies the space complexity of parallel simulation. Our goal is to design an efficient memory management protocol which guarantees that the memory consumption of parallel simulation is of the same order as sequential simulation. (Such an algorithm is referred to as a optimal .) First, we derive the relationships among the space complexities of sequential simulation, Chandy-Misra simulation [2], and Time Warp simulation [7]. We show that Chandy-Misra may consume more storage than sequential simulation, or vice versa. Then we show that Time Warp never consumes less memory than sequential simulation. Then we describe cancelback , an optimal Time Warp memory management protocol proposed by Jefferson. Although cancelback is considered to be complete solution for the storage management problem in Time Warp, some efficiency issues in implementing this algorithm must be considered. We propose an optimal algorithm called artifical rollback . We show that this algorithm is easy to implement and analyze. An implementation of artificial rollback is given, which is integrated with processor scheduling to adjust the memory consumption rate based on the amount of free storage available in the system.