Abstract
The road to successful management of a large research and development (R&D) project requires comprehensive and flexible capabilities to foster effective and timely communication, tracking, and decision-making. Best practices developed and employed by the Exascale Computing Project (ECP) afford a comprehensive example of management practices that benefit this type of a large-scale, physically dispersed R&D project. This article will summarize the ECP’s hybrid approach to project management, which incorporates principles of the Department of Energy (DOE) order for the management of large capital asset projects (DOE O 413.3b) and elements of industry-standard Agile practices, as well as the tools that promote extensive collaborative endeavors. Using a hybrid approach to managing project elements is a key tenet within the ECP and is implemented in part by ensuring that information such as detailed technical plans and achievements, budget and cost information, milestone creation, and progress metrics are readily accessible to all participants. The functionality to enable this broad, dynamic access is provided by a variety of essential and flexible tools, which the ECP has found to be invaluable in managing work and communicating with project team members and stakeholders. The strong integration of R&D efforts results in a dynamic environment in which frequent input from management, collaborators, and stakeholders is essential. This overall approach provides the guidelines and policies, processes, information, tools and services, and output that are necessary for the effective management of large, complex projects. Such an approach may also be applied to smaller, less complex projects for a similar outcome.
| Original language | English |
|---|---|
| Title of host publication | Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI - 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Revised Selected Papers |
| Editors | Jeffrey Nichols, Arthur ‘Barney’ Maccabe, Suzanne Parete-Koon, Becky Verastegui, Oscar Hernandez, Theresa Ahearn |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 381-393 |
| Number of pages | 13 |
| ISBN (Print) | 9783030633929 |
| DOIs | |
| State | Published - 2021 |
| Event | 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020 - Virtual, Online Duration: Aug 26 2020 → Aug 28 2020 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 1315 CCIS |
| ISSN (Print) | 1865-0929 |
| ISSN (Electronic) | 1865-0937 |
Conference
| Conference | 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020 |
|---|---|
| City | Virtual, Online |
| Period | 08/26/20 → 08/28/20 |
Funding
Acknowledgements. This work was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. K. Boudwin et al.—Contributed Equally. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
