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Groer, Christopher S.

Publications and source records attributed to Groer, Christopher S..

Utility functions and resource management in an oversubscribed heterogeneous computing environment

We model an oversubscribed heterogeneous computing system where tasks arrive dynamically and a scheduler maps the tasks to machines for execution. The environment and workloads are based on those being investigated by the Extreme Scale Systems Center at Oak Ridge National Laboratory. Utility functions that are designed based on specifications from the system owner and users are used to create a metric for the performance of resource allocation heuristics. Each task has a time-varying utility (importance) that the enterprise will earn based on when the task successfully completes execution. We design multiple heuristics, which include a technique to drop low utility-earning tasks, to maximize the total utility that can be earned by completing tasks. The heuristics are evaluated using simulation experiments with two levels of oversubscription. The results show the benefit of having fast heuristics that account for the importance of a task and the heterogeneity of the environment when making allocation decisions in an oversubscribed environment. Furthermore, the ability to drop low utility-earning tasks allow the heuristics to tolerate the high oversubscription as well as earn significant utility.

97 MATHEMATICS AND COMPUTING↗

Real Time Simulation of Power Grid Disruptions

DOE-OE and DOE-SC workshops (Reference 1-3) identified the key power grid problem that requires insight addressable by the next generation of exascale computing is coupling of real-time data streams (1-2 TB per hour) as the streams are ingested to dynamic models. These models would then identify predicted disruptions in time (2-4 seconds) to trigger the smart grid s self healing functions. This project attempted to establish the feasibility of this approach and defined the scientific issues, and demonstrated example solutions to important smart grid simulation problems. These objectives were accomplished by 1) using the existing frequency recorders on the national grid to establish a representative and scalable real-time data stream; 2) invoking ORNL signature identification algorithms; 3) modeling dynamically a representative region of the Eastern interconnect using an institutional cluster, measuring the scalability and computational benchmarks for a national capability; and 4) constructing a prototype simulation for the system s concept of smart grid deployment. The delivered ORNL enduring capability included: 1) data processing and simulation metrics to design a national capability justifying exascale applications; 2) Software and intellectual property built around the example solutions; 3) demonstrated dynamic models to design few second self-healing.

Chinthavali, Supriya↗

Parallel Algorithms for Graph Optimization Using Tree Decompositions

Although many $\cal{NP}$-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of the necessary dynamic programming tables and excessive runtimes of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree decomposition-based approach to solve the maximum weighted independent set problem. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.

99 GENERAL AND MISCELLANEOUS↗