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All eyes on the conductor

February 13, 2016
The Agency for Science, Technology and Research (A*STAR)
A ‘conductor’ that ensures simultaneous processing tasks keep time could dramatically increase the efficiency of ‘cloud’ simulations, report scientists.

A 'conductor' that ensures simultaneous processing tasks keep time could dramatically increase the efficiency of 'cloud' simulations.

In large-scale simulations that involve simultaneous computational tasks on distributed computers, the overall speed of the simulation is limited by the slowest link. By adaptively redistributing computational resources in real-time according to workload, a Singapore-based research team have shown how to overcome this 'slowest link' limitation.

This approach could dramatically improve the speed and efficiency of simulations conducted across many computers -- also called 'cloud' simulations.

"The problem of workload imbalance is very common in large-scale simulations, which involve a group of parallel distributed computers or 'components' that need to synchronize with each other to ensure that all simulation events are executed in time stamp order," explains research leader Zengxiang Li, from the A*STAR Institute of High Performance Computing.

Parallel computing simulations involve a large number of events that must occur in order. These events are assigned to multiple parallel computing 'nodes' for simultaneous computation. When an event is processed, new events may be generated and inserted into the event processing queue. It is wasteful to let expensive computational resources lie idle waiting for work, so parallel processing schemes often allow each node to process events sequentially without waiting for events from other nodes.

The problem is that if events from one node are late, the other nodes proceeding with their 'optimistic' execution of the next event will need to discard their extra work and rollback to where the late node left off. "The entire simulation execution is held back by the slowest components," says Li, "while faster components risk wasting time and resources on overoptimistic execution and execution rollbacks."

To improve the efficiency of such simulations, Li and his colleagues developed a resource-conducting scheme called Adaptive Resource Provisioning Mechanism in Virtual Execution Environments, or ArmVee. This scheme sits transparently as middleware in the simulation environment to monitor workloads and task completion speeds on each node in real-time. ArmVee then dynamically reallocates resources, such as memory and processing cycles, to speed up the slowest links.

"We use a self-adaptive auto-regressive-moving-average model -- commonly used in control theory -- to capture the relationship between simulation performance and resources," says Li. "This allows ArmVee to predict the dynamically changing simulation workload and to align the execution speeds of simulation components proactively so that each advances in simulation time with comparable speed."

Importantly, ArmVee can be used transparently in standard simulation architectures without any simulation recoding or interruption. This makes it ready for implementation in standard parallel and distributed simulations.

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Materials provided by The Agency for Science, Technology and Research (A*STAR). Note: Content may be edited for style and length.

Journal Reference:

  1. Zengxiang Li, Wentong Cai, Stephen John Turner, Xiaorong Li, Ta Nguyen Binh Duong, Rick Siow Mong Goh. Adaptive Resource Provisioning Mechanism in VEEs for Improving Performance of HLA-Based Simulations. ACM Transactions on Modeling and Computer Simulation, 2015; 26 (1): 1 DOI: 10.1145/2717309

Cite This Page:

The Agency for Science, Technology and Research (A*STAR). "All eyes on the conductor." ScienceDaily. ScienceDaily, 13 February 2016. <>.
The Agency for Science, Technology and Research (A*STAR). (2016, February 13). All eyes on the conductor. ScienceDaily. Retrieved June 15, 2024 from
The Agency for Science, Technology and Research (A*STAR). "All eyes on the conductor." ScienceDaily. (accessed June 15, 2024).

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