A Communication- and Memory-Aware Model for Load Balancing Tasks
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Publications and source records attributed to Lifflander, Jonathan Josiah.
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This report presents our work to model the workloads of a linear electromagnetic application based on the method of moments in the frequency domain to effectively load balance the matrix assembly. This application is particularly challenging to load balance due to its lack of persistent iterative behavior, its operation under tight memory constraint (where the matrix may fill 80% of memory on each node), and the algorithmic complexity of the computational method. This report describes the first step in our work to apply an inspector-executor approach for load balancing workloads where key parameters are exposed during the inspector phase and a pre-trained model is applied to predict relative task weights for the load balancer.
The goal of this report is to provide insight to the development of vt-tv, a C++ HPC visualization tool designed for insightful analysis of load-balancing metrics in the DARMA toolkit. In particular, it delves into its modular data model and diverse usage scenarios, emphasizing adaptability and efficiency.
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The goal of this report is to illustrate the use of Sandia's Automatic Report Generator (ARG), when applied to an Electrostatic simulation case run with Sandia's EMPIRE code. It documents the results of a hackathon session that was held at the March 19-22 DOE Workshop Workflow and Hackathon that was held in Livermore, where the co-authors demonstrated ARG's flexibilty by extending it to several aspect of such simulation in less than a day's worth of work. The Explorator component of ARG automatically picks up the case's input deck, hereby determining the data components that the Generator and Assembler components are currently able to document: meta-data, input deck, mesh, and solution fields. The ARG is not yet capable of documenting the particles file created by the simulation, which will require further work.