S. Chandrasekaran and M. D. Hill. Optimistic simulation of parallel architectures using program executables. In Proceedings of 10th Workshop on Parallel and Distributed Simulation (PADS'96), 1996.  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... [9, 13, 14] However, even with the use of abstract models and direct execution, sequential program simulators tended to be slow with slowdown factors ranging from 2 to 35 for each process in the simulated program [9] Several recent efforts have been exploring the use of parallel execution [10, 17, 18, 24, 25, 28, 29] to reduce the model execution times, with varying degrees of success. In order to have multiple simulation processes and maintain accuracy, simulations use protocols to synchronize the processes. One of the widely used protocols is the Quantum protocol, which lets the processes compute for a ....

S. Chandrasekaran and M. D. Hill. Optimistic simulation of parallel architectures using program executables. In Proceedings of 10th Workshop on Parallel and Distributed Simulation (PADS'96), 1996.

.... [9, 13, 14] However, even with the use of abstract models and direct execution, sequential program simulators tended to be slow with slowdown factors ranging from 2 to 35 for each process in the simulated program [9] Several recent efforts have been exploring the use of parallel execution [10, 17, 18, 24, 25, 28, 29] to reduce the model execution times, with varying degrees of success. In order to have multiple simulation processes and maintain accuracy, simulations use protocols to synchronize the processes. One of the widely used protocols is the Quantum protocol, which lets the processes compute for a ....

S. Chandrasekaran and M. D. Hill. Optimistic simulation of parallel architectures using program executables. In Proceedings of 10th Workshop on Parallel and Distributed Simulation (PADS'96), 1996.

....portions of code directly on the architecture being studied. The application is compiled for the instruction set architecture of the machine, but the simulator traps all calls that interact with the simulated component. Research in optimistic simulation [12] of shared memory was performed in [5]. This work looked into a directexecution simulation implemented using incremental statesaving for both an aggressive Time Warp like mechanism as well as a combination of a conservative and a Breathing Time Buckets based optimistic engine. For both cases their experiments ended in negative ....

....[24] which requires the runtime system to maintain a log of only the state changes rather than the whole state. A wellknown disadvantage to this is that upon roll back, the current state must be reconstructed from previous logs entries, a detrimental effect that was experimentally observed in [5]. Furthermore, this approach may not work for scientific programs because the large amounts of memory required by their datasets may already be prohibitively large. A third alternative is that (3) we can use a compiler assisted optimization wherein large portions of code and memory are excised ....

S. Chandrasekaran and M. Hill. "Optimistic Simulation of Parallel Architectures Using Program Executables," Workshop on Parallel and Distributed Simulation, May 1996.

.... designed for sequential execution [8, 12, 13] However, even with the use of direct execution, sequential program simulators tended to be slow with slowdown factors ranging from 2 to 35 for each process in the simulated program [8] Several efforts have been exploring the use of parallel execution [10, 14, 17, 19, 22] to reduce the model execution times, with varying degrees of success. Many such simulators use sequential or parallel implementations of the quantum protocol. In order to support multiple simulation processes (possibly executing on multiple processors) and maintain accuracy, parallel simulation ....

S. Chandrasekaran and M. D. Hill, "Optimistic simulation of parallel architectures using program executables," PADS, 1996.

.... [9, 13, 14] However, even with the use of abstract models and direct execution, sequential program simulators tended to be slow with slowdown factors ranging from 2 to 35 for each process in the simulated program [9] Several recent efforts have been exploring the use of parallel execution [10, 16, 17, 23, 24, 27, 28] to reduce the model execution times, with varying degrees of success. In order to have multiple simulation processes and maintain accuracy, simulations use protocols to synchronize the processes. One of the widely used protocols is the Quantum protocol, which lets the processes compute for a ....

S. Chandrasekaran and M. D. Hill, "Optimistic simulation of parallel architectures using program executables," Proceedings of Tenth Workshop on Parallel and Distributed Simulation., 1996.

....research was supported in part by an ARPA CSTO Award (No. F30602 94 C 0273) 1 tended to be slow with slowdown factors ranging from 2 to 35 for each process in the simulated program[BDCW91] Several recent e orts have been exploring the use of parallel execution[LW96, RHL 93, DHN94, PB95, CH96] to reduce the model execution times, with varying degrees of success. In this paper, we describe a parallel simulator, which can model the behavior of parallel programs using conservative synchronization algorithms [Mis86] The main contributions of this paper are as follows: We address the ....

S. Chandrasekaran and M.D. Hill. Optimistic simulation of parallel architectures using program executables. In 10th Workshop on Parallel and Distributed Simulation PADS96, pages 143-150, May 1996.

.... Parts of this work were previously reported in [PB95] and [PB98] 1 simulators tended to be slow with slowdown factors ranging from 2 to 35 for each process in the simulated program[BDCW91] Several recent efforts have been exploring the use of parallel execution[LW96, RHL 93, DHN94, PB95, CH96] to reduce the model execution times, with varying degrees of success. Our simulator, MPI SIM, is capable of simulating a set of core MPI [GL93] functions such as non blocking, synchronous or buffered sends and non blocking receives. These are the building blocks of more complex point to point ....

S. Chandrasekaran and M.D. Hill. Optimistic simulation of parallel architectures using program executables. In 10th Workshop on Parallel and Distributed Simulation PADS96, pages 143--150, May 1996.

....Little effort was made in this direction in the work reported here; it will be undertaken when availability of a larger platform makes it practical. 6 Related Work Numerous groups have developed simulators for multiprocessor architectures. A few of them are surveyed here. The Wisconsin Wind Tunnel[3] uses direct execution of instrumented programs on a CM 5, resulting in very fast and accurate simulation. Interactions between nodes occur only when programs access shared memory locations, which are translated by the underlying simulation system into message passing events between CM 5 nodes. ....

Chandrasekaran, S., and Hill, M. D. Optimistic Simulation of Parallel Architectures Using Program Executables. In Proceedings of the 10th Workshop on Parallel and Distributed Simulation (May 1996), pp. 143--150.

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