Benchmarking Memory Management Capabilities within ROOT-Sim

In parallel discrete event simulation techniques, the simulation model is partitioned into objects, concurrently executing events on different CPUs and/or multiple CPUCores.In such a context, run-time supports for logical time synchronization across the different simulation objectsplay a central role in determining the effectiveness of the specific parallel simulation environment. In this paper we present an experimental evaluation of the memory management capabilities offered by the ROme OpTimistic Simulator (ROOT-Sim). This is an open source parallel simulation environment transparently supporting optimistic synchronization via recoverability (based on incremental log/restore techniques) of any type of memory operation affecting the state of simulation objects, i.e., memory allocation, deallocation and update operations. The experimental study is based on a synthetic benchmark which mimics different read/write patterns inside the dynamic memory map associated with the state of simulation objects. This allows sensibility analysis of time and space effects due to the memory management subsystem while varying the type and the locality of the accesses associated with event processing.

[1]  Jeffrey F. Naughton,et al.  Low-Latency, Concurrent Checkpointing for Parallel Programs , 1994, IEEE Trans. Parallel Distributed Syst..

[2]  K. Arvind,et al.  Probabilistic Clock Synchronization in Distributed Systems , 1994, IEEE Trans. Parallel Distributed Syst..

[3]  Roberto Vitali,et al.  Di-DyMeLoR: Logging only Dirty Chunks for Efficient Management of Dynamic Memory Based Optimistic Simulation Objects , 2009, 2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation.

[4]  R. M. Fujimoto,et al.  Parallel discrete event simulation , 1989, WSC '89.

[5]  Francesco Quaglia,et al.  Nonblocking Checkpointing for Optimistic Parallel Simulation: Description and an Implementation , 2003, IEEE Trans. Parallel Distributed Syst..

[6]  Johan Montagnat,et al.  Transparent incremental state saving in time warp parallel discrete event simulation , 1996, Workshop on Parallel and Distributed Simulation.

[7]  Francesco Quaglia.  A Cost Model for Selecting Checkpoint Positions in Time Warp Parallel Simulation , 2001, IEEE Trans. Parallel Distributed Syst..

[8]  Francesco Quaglia,et al.  DyMeLoR: Dynamic Memory Logger and Restorer Library for Optimistic Simulation Objects with Generic Memory Layout , 2008, 2008 22nd Workshop on Principles of Advanced and Distributed Simulation.

[9]  Philip A. Wilsey,et al.  WARPED: a time warp simulation kernel for analysis and application development , 1996, Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences.

[10]  Richard M. Fujimoto,et al.  GTW: a time warp system for shared memory multiprocessors , 1994, Proceedings of Winter Simulation Conference.

[11]  Philip A. Wilsey,et al.  An analytical comparison of periodic checkpointing and incremental state saving , 1993, PADS '93.

[12]  Rassul Ayani,et al.  Adaptive checkpointing in Time Warp , 1994, PADS '94.

[13]  Adel Said Elmaghraby,et al.  An Analytical Model for Hybrid Checkpointing in Time Warp Distributed Simulation , 1998, IEEE Trans. Parallel Distributed Syst..

[14]  Darrin West,et al.  Automatic incremental state saving , 1996, Workshop on Parallel and Distributed Simulation.

[15]  Francesco Quaglia,et al.  Transparent State Management for Optimistic Synchronization in the High Level Architecture , 2005, Workshop on Principles of Advanced and Distributed Simulation (PADS'05).

[16]  Robert Rönngren,et al.  Event sensitive state saving in time warp parallel discrete event simulations , 1996, WSC.

[17]  Francesco Quaglia,et al.  A version of MASM portable across different UNIX systems and different hardware architectures , 2005, Ninth IEEE International Symposium on Distributed Simulation and Real-Time Applications.