Engineering topics

Kennedy, R.

Publications and source records attributed to Kennedy, R..

7 records

DOE OSTI2017

Experience in using commercial clouds in CMS

Historically high energy physics computing has been performed on large purpose-built computing systems. In the beginning there were single site computing facilities, which evolved into the Worldwide LHC Computing Grid (WLCG) used today. The vast majority of the WLCG resources are used for LHC computing and the resources are scheduled to be continuously used throughout the year. In the last several years there has been an explosion in capacity and capability of commercial and academic computing clouds. Cloud resources are highly virtualized and intended to be able to be flexibly deployed for a variety of computing tasks. There is a growing interest amongst the cloud providers to demonstrate the capability to perform large scale scientific computing. In this presentation we will discuss results from the CMS experiment using the Fermilab HEPCloud Facility, which utilized both local Fermilab resources and Amazon Web Services (AWS). The goal was to work with AWS through a matching grant to demonstrate a sustained scale approximately equal to half of the worldwide processing resources available to CMS. We will discuss the planning and technical challenges involved in organizing the most IO intensive CMS workflows on a large-scale set of virtualized resource provisioned by the Fermilab HEPCloud. We will describe the data handling and data management challenges. Also, we will discuss the economic issues and cost and operational efficiency comparison to our dedicated resources. At the end we will consider the changes in the working model of HEP computing in a domain with the availability of large scale resources scheduled at peak times.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Virtual machine provisioning, code management, and data movement design for the Fermilab HEPCloud Facility

The Fermilab HEPCloud Facility Project has as its goal to extend the current Fermilab facility interface to provide transparent access to disparate resources including commercial and community clouds, grid federations, and HPC centers. This facility enables experiments to perform the full spectrum of computing tasks, including data-intensive simulation and reconstruction. We have evaluated the use of the commercial cloud to provide elasticity to respond to peaks of demand without overprovisioning local resources. Full scale data-intensive workflows have been successfully completed on Amazon Web Services for two High Energy Physics Experiments, CMS and NOνA, at the scale of 58000 simultaneous cores. This paper describes the significant improvements that were made to the virtual machine provisioning system, code caching system, and data movement system to accomplish this work. The virtual image provisioning and contextualization service was extended to multiple AWS regions, and to support experiment-specific data configurations. A prototype Decision Engine was written to determine the optimal availability zone and instance type to run on, minimizing cost and job interruptions. We have deployed a scalable on-demand caching service to deliver code and database information to jobs running on the commercial cloud. It uses the frontiersquid server and CERN VM File System (CVMFS) clients on EC2 instances and utilizes various services provided by AWS to build the infrastructure (stack). We discuss the architecture and load testing benchmarks on the squid servers. We also describe various approaches that were evaluated to transport experimental data to and from the cloud, and the optimal solutions that were used for the bulk of the data transport. Finally, we summarize lessons learned from this scale test, and our future plans to expand and improve the Fermilab HEP Cloud Facility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

The HEPCloud Facility: elastic computing for High Energy Physics – The NOvA Use Case

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 25 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.

Fuess, S.↗

DOE OSTI2013

Separate effects identification via casting process modeling for experimental measurement of U–Pu–Zr alloys

Computational simulations of gravity casting processes for metallic U–Pu–Zr nuclear fuel rods have been performed using a design-of-experiments technique to determine the fluid flow, liquid heat transfer, and solid heat transfer parameters which most strongly influence the process solidification speed and fuel rod porosity. The results are used to make recommendations for the best investment of experimental time and effort to measure process parameters.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

Report of Separate Effects Testing for Modeling of Metallic Fuel Casting Process

In order to give guidance regarding the best investment of time and effort in experimental determination of parameters defining the casting process, a Flow-3D model of the casting process was used to investigate the most influential parameters regarding void fraction of the solidified rods and solidification speed for fluid flow parameters, liquid heat transfer parameters, and solid heat transfer parameters. Table 1 summarizes the most significant variables for each of the situations studied. A primary, secondary, and tertiary effect is provided for fluid flow parameters (impacts void fraction) and liquid heat transfer parameters (impacts solidification). In Table 1, the wetting angle represents the angle between the liquid and mold surface as pictured in Figure 1. The viscosity is the dynamic viscosity of the liquid and the surface tension is the property of the surface of a liquid that allows it to resist an external force. When only considering solid heat transfer properties, the variations from case to case were very small. Details on this conclusion are provided in the section considering solid heat transfer properties. The primary recommendation of the study is to measure the fluid flow parameters, specifically the wetting angle, surface tension, and dynamic viscosity, in order of importance, as well as the heat transfer parameters latent heat and specific heat of the liquid alloy. The wetting angle and surface tension can be measured simultaneously using the sessile drop method. It is unclear whether there is a temperature dependency in these properties. Thus measurements for all three parameters are requested at 1340, 1420, and 1500 degrees Celsius, which correspond to the minimum, middle, and maximum temperatures of the liquid alloy during the process. In addition, the heat transfer coefficient between the mold and liquid metal, the latent heat of transformation, and the specific heat of the liquid metal all have strong influences on solidification. These parameters should be measured to achieve better simulation fidelity. Information on all the mentioned parameters is virtually nonexistent. Presently, all the parameters within the casting model are estimates based on pure U, or another alloy such as U-Ni.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Wind Power Plant SCADA and Controls

Modern Wind Power Plants (WPPs) contain a variety of intelligent electronic devices (IEDs), Supervisory Control and Data Acquisition (SCADA) and communication systems. This paper discusses the issues related to a typical WPP's SCADA and Control. Presentation topics are: (1) Wind Turbine Controls; (2) Wind Plant SCADA, OEM SCADA Solutions, Third-Party SCADA Solutions; (3) Wind Plant Control; and (4) Security and Reliability Compliance.

17 WIND ENERGY↗

NASA NTRS1977

The first Spacelab payload - A joint NASA/ESA venture

Planning for the 1980 qualification flight of Spacelab, which will involve a long module and one pallet, is discussed. The mission will employ two payload specialists, one sponsored by NASA and the other by ESA. Management of the Spacelab mission functions, including definition and execution of the on-board experiments, development of the experimental hardware and training of the payload specialists, is considered; studies proposed in the areas of atmospheric physics, space plasma physics, solar physics, earth observations, astronomy, astrophysics, life sciences and material sciences are reviewed. Analyses of the Spacelab environment and the Spacelab-to-orbiter and Spacelab-to-experiment interactions are also planned.

Kennedy, R.↗