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Moibenko, Alexander

Publications and source records attributed to Moibenko, Alexander.

HEPCloud, an Elastic Hybrid HEP Facility using an Intelligent Decision Support System

HEPCloud is rapidly becoming the primary system for provisioning compute resources for all Fermilab-affiliated experiments. In order to reliably meet the peak demands of the next generation of High Energy Physics experiments, Fermilab must plan to elastically expand its computational capabilities to cover the forecasted need. Commercial cloud and allocation-based High Performance Computing (HPC) resources both have explicit and implicit costs that must be considered when deciding when to provision these resources, and at which scale. In order to support such provisioning in a manner consistent with organizational business rules and budget constraints, we have developed a modular intelligent decision support system (IDSS) to aid in the automatic provisioning of resources spanning multiple cloud providers, multiple HPC centers, and grid computing federations. In this paper, we discuss the goals and architecture of the HEPCloud Facility, the architecture of the IDSS, and our early experience in using the IDSS for automated facility expansion both at Fermi and Brookhaven National Laboratory.

Mhashilkar, Parag↗

Intelligently-Automated Facilities Expansion with the HEPCloud Decision Engine

The next generation of High Energy Physics experiments are expected to generate exabytes of data---two orders of magnitude greater than the current generation. In order to reliably meet peak demands, facilities must either plan to provision enough resources to cover the forecasted need, or find ways to elastically expand their computational capabilities. Commercial cloud and allocation-based High Performance Computing (HPC) resources both have explicit and implicit costs that must be considered when deciding when to provision these resources, and to choose an appropriate scale. In order to support such provisioning in a manner consistent with organizational business rules and budget constraints, we have developed a modular intelligent decision support system (IDSS) to aid in the automatic provisioning of resources---spanning multiple cloud providers, multiple HPC centers, and grid computing federations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Fermilab HEPCloud Facility Decision Engine Design

The Decision Engine is a critical component of the HEP Cloud Facility. It provides the functionality of resource scheduling for disparate resource providers, including those which may have a cost or a restricted allocation of cycles. Along with the architecture, design, and requirements for the Decision Engine, this document will provide the rationale and explanations for various design decisions. In some cases, requirements and interfaces for a limited subset of external services will be included in this document. This document is intended to be a high level design. The design represented in this document is not complete and does not break everything down in detail. The class structures and pseudo-code exist for example purposes to illustrate desired behaviors, and as such, should not be taken literally. The protocols and behaviors are the important items to take from this document. This project is still in prototyping mode so flaws and inconsistencies may exist and should be noted and treated as failures.

97 MATHEMATICS AND COMPUTING↗