TY - GEN
T1 - Phoenix
T2 - 2022 Conference on Practice and Experience in Advanced Research Computing: Revolutionary: Computing, Connections, You, PEARC 2022
AU - Jezghani, Aaron
AU - Sarajlic, Semir
AU - Brandon, Michael
AU - Bright, Neil
AU - Belgin, Mehmet
AU - Beyer, Gergory
AU - Blanton, Christopher
AU - Buffington, Pam
AU - Coulter, J. Eric
AU - Lara, Ruben
AU - Lefton, Lew
AU - Leonard, David
AU - Liu, Fang Cherry
AU - Manalo, Kevin
AU - Manno, Paul
AU - Moseley, Craig
AU - Nightingale, Trever
AU - Bonner, N. Bray
AU - Rahaman, Ronald
AU - Stone, Christopher
AU - Suda, Kenneth J.
AU - Wan, Peter
AU - Weiner, Michael D.
AU - Womack, Deirdre
AU - Zhang, Nuyun
AU - Zhou, Dan
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/7/8
Y1 - 2022/7/8
N2 - Originating from partnerships formed by central IT and researchers supporting their own clusters, the traditional condominium and dedicated cluster models for research computing are appealing and prevalent among emerging centers throughout academia. In 2008, Georgia Institute of Technology (GT) launched a campus strategy to centralize the hosting of computing resources across multiple science and engineering disciplines under a group of expert support personnel, and in 2009 the Partnership for an Advanced Computing Environment (PACE) was formed. Due to the increases in scale over the past decade, however, the initial models created challenges for the research community, systems administrators, and GT's leadership. In 2020, GT launched a strategic initiative to revitalize research computing through a refresh of the infrastructure and computational resources in parallel with the migration to a new state-of-the-art datacenter, Coda, followed by the transition to a new consumption-based cost model. These efforts have resulted in an overall increase in cluster utilization, access to more hardware, a decrease in queue wait times, a reduction in resource provision times, and increase in return on investment, suggesting that such a model is highly advantageous for academic research computing centers. Presented here are the methods employed in making the change to the new cost model, data supporting these claims, and the ongoing improvements to continue meeting the needs of the GT research community whose research is accelerated by the deployment of the new cost model and the Phoenix cluster that ranked #277 on the Top500 November 2020 list.
AB - Originating from partnerships formed by central IT and researchers supporting their own clusters, the traditional condominium and dedicated cluster models for research computing are appealing and prevalent among emerging centers throughout academia. In 2008, Georgia Institute of Technology (GT) launched a campus strategy to centralize the hosting of computing resources across multiple science and engineering disciplines under a group of expert support personnel, and in 2009 the Partnership for an Advanced Computing Environment (PACE) was formed. Due to the increases in scale over the past decade, however, the initial models created challenges for the research community, systems administrators, and GT's leadership. In 2020, GT launched a strategic initiative to revitalize research computing through a refresh of the infrastructure and computational resources in parallel with the migration to a new state-of-the-art datacenter, Coda, followed by the transition to a new consumption-based cost model. These efforts have resulted in an overall increase in cluster utilization, access to more hardware, a decrease in queue wait times, a reduction in resource provision times, and increase in return on investment, suggesting that such a model is highly advantageous for academic research computing centers. Presented here are the methods employed in making the change to the new cost model, data supporting these claims, and the ongoing improvements to continue meeting the needs of the GT research community whose research is accelerated by the deployment of the new cost model and the Phoenix cluster that ranked #277 on the Top500 November 2020 list.
KW - HPC
KW - cluster
KW - cost model
KW - datacenter
UR - https://www.scopus.com/pages/publications/85135225476
U2 - 10.1145/3491418.3530767
DO - 10.1145/3491418.3530767
M3 - Conference contribution
AN - SCOPUS:85135225476
T3 - PEARC 2022 Conference Series - Practice and Experience in Advanced Research Computing 2022 - Revolutionary: Computing, Connections, You
BT - PEARC 2022 Conference Series - Practice and Experience in Advanced Research Computing 2022 - Revolutionary
PB - Association for Computing Machinery, Inc
Y2 - 10 July 2022 through 14 July 2022
ER -