![Sample our Economics, Finance,Business & Industry journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5931/TOC-Subject-Sample-2021-Economics-Finance-Business-Industry.jpg"})
Abstract
It is well known that Parallel Discrete Event Simulation systems may suffer, in terms of delivered performance, from imbalance of the computational load. In case of conservative synchronization we may experience CPU under-utilization and/or excessive communication overhead. On the other hand, for the optimistic paradigm we may even have rollback thrashing effects, with a consequent reduction of the percentage of productive (ie not rolled back) work carried out. This paper presents the design of a global memory management architecture supporting application-transparent migration of simulation objects whose state is scattered across dynamically allocated memory chunks. Our approach is based on a non-intrusive background protocol that provides each instance of the simulation kernel with information on the current mapping of the virtual address space of all the other instances. Dynamic memory requests by the application layer are then locally mapped onto virtual-address ranges that maximize the likelihood of being portable onto the address space of a remote kernel instance. In this way, independently of the load-balancing trigger (or policy), we maximize the likelihood that a desirable migration across a specific couple of kernels can actually take place due to compliance of the corresponding source/destination address spaces. We have integrated the global memory manager within the ROme OpTimistic Simulator (ROOT-Sim), namely a run-time environment based on the optimistic synchronization paradigm which automatically and transparently parallelizes the execution of event-handler-based simulation programs conforming to ANSI-C. Further, we provide a contribution in the direction of widening load-balancing schemes for optimistic simulation systems by defining migration triggers and selection policies for the objects to be migrated on the basis of memory usage patterns. An experimental assessment of the architecture and of memory-oriented load balancing is also provided.
* An earlier version of this article by the same authors, with title ‘Application Transparent Migration of Simulation Objects with Generic Memory Layout’, appeared in the proceedings of PADS 2011.
1 Full logs for a given simulation object are taken sparsely even when the autonomic log/restore subsystem provided by ROOT-Sim switches to the incremental log mode for that object. This is done to optimize restore operations.
2 Reverse computing approaches (see, eg, CitationCarothers et al, 1999) have recently tackled this issue by reducing the memory demand for state-log buffers. However, the memory demand problem remains central, especially in contexts where reverse computing is not, or not easily, applicable.
3 In this case, pre-reserving is only performed by the Memory Map Manager and, as discussed in Section 4, operated at the level of blocks of memory got from the allocator, and destined to chunks to be delivered to a specific simulation object.
4 Compared to the previous test cases, this time we have non-homogeneous event costs across the cells due to increase of the workload on a subset of them, which is the reason why we prefer Wall-Clock-Time as the performance indicator, compared to the event rate.
* An earlier version of this article by the same authors, with title ‘Application Transparent Migration of Simulation Objects with Generic Memory Layout’, appeared in the proceedings of PADS 2011.
1 Full logs for a given simulation object are taken sparsely even when the autonomic log/restore subsystem provided by ROOT-Sim switches to the incremental log mode for that object. This is done to optimize restore operations.
2 Reverse computing approaches (see, eg, CitationCarothers et al, 1999) have recently tackled this issue by reducing the memory demand for state-log buffers. However, the memory demand problem remains central, especially in contexts where reverse computing is not, or not easily, applicable.
3 In this case, pre-reserving is only performed by the Memory Map Manager and, as discussed in Section 4, operated at the level of blocks of memory got from the allocator, and destined to chunks to be delivered to a specific simulation object.
4 Compared to the previous test cases, this time we have non-homogeneous event costs across the cells due to increase of the workload on a subset of them, which is the reason why we prefer Wall-Clock-Time as the performance indicator, compared to the event rate.
Notes
* An earlier version of this article by the same authors, with title ‘Application Transparent Migration of Simulation Objects with Generic Memory Layout’, appeared in the proceedings of PADS 2011.
1 Full logs for a given simulation object are taken sparsely even when the autonomic log/restore subsystem provided by ROOT-Sim switches to the incremental log mode for that object. This is done to optimize restore operations.
2 Reverse computing approaches (see, eg, CitationCarothers et al, 1999) have recently tackled this issue by reducing the memory demand for state-log buffers. However, the memory demand problem remains central, especially in contexts where reverse computing is not, or not easily, applicable.
3 In this case, pre-reserving is only performed by the Memory Map Manager and, as discussed in Section 4, operated at the level of blocks of memory got from the allocator, and destined to chunks to be delivered to a specific simulation object.
4 Compared to the previous test cases, this time we have non-homogeneous event costs across the cells due to increase of the workload on a subset of them, which is the reason why we prefer Wall-Clock-Time as the performance indicator, compared to the event rate.