Usage Report sierra

• Period: November 13 – May 13, 2014
• Hostname: sierra.futuregrid.org
• Services: nimbus, openstack, eucalyptus
• Metrics: VMs count, Users count, Wall time (hours), Distribution by wall time, project, project leader, and institution, and systems

Histogram

Summary (Monthly)

Figure 1: Average monthly usage data (wall time (hour), launched VMs, users)

This mixed chart represents average monthly usage as to wall time (hour), the number of VM instances and active users.

• Period: November 13 – May 13, 2014

• Cloud(IaaS): nimbus, openstack, eucalyptus

• Hostname: sierra

• Metric:

  • Runtime (Wall time hours): Sum of time elapsed from launch to termination of VM instances
  • Count (VM count): The number of launched VM instances
  • User count (Active): The number of users who launched VMs

Summary (Daily)

Figure 2: Users count

This time series chart represents daily active user count for cloud services and shows historical changes during the period.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

Figure 3: VMs count

This time series chart represents the number of daily launched VM instances for cloud services and shows historical changes during the period.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

Figure 4: Wall time (hours)

This time series chart represents daily wall time (hours) for cloud services and shows historical changes during the period.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

Distribution

Figure 5: VM count by wall time

This chart illustrates usage patterns of VM instances in terms of running wall time.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

Figure 6: VMs count by project

This chart illustrates the proportion of launched VM instances by project groups. The same data in tabular form follows.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

VMs count by project

Project	Value
fg-174:RAIN: FutureGrid Dynamic provisioning Framework	1069
fg-40:Inca	848
fg-54:Investigating cloud computing as a solution for analyzing particle physics data	426
fg-298:FRIEDA: Flexible Robust Intelligent Elastic Data Management	337
fg-371:Characterizing Infrastructure Cloud Performance for Scientific Computing	219
fg-367:Optimize rapid deployment and updating of VM images at the remote compute cluster	218
fg-362:Course: Cloud Computing and Storage (UF)	168
fg-172:Cloud-TM	158
fg-82:FG General Software Development	142
fg-224:Nimbus Auto Scale	138
fg-389:Investigating the Apache Big Data Stack	108
fg-384:Graph/network analysis Resource manager	56
fg-355:Course: Data Center Scale Computing Class	54
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters	48
fg-10:TeraGrid XD TIS(Technology Insertion Service) Technology Evaluation Laboratory	40
fg-168:Next Generation Sequencing in the Cloud	37
fg-165:The VIEW Project	31
fg-363:Course: Applied Cyberinfrastructure concepts	21
fg-175:GridProphet, A workflow execution time prediction system for the Grid	16
fg-214:Mining Interactions between Network Community Structure and Information Diffusion	15
fg-374:Course: Cloud and Distributed Computing	15
fg-382:Reliability Analysis using Hadoop and MapReduce	12
fg-372:Mobile Device Computation Offloading over SocialVPNs	12
fg-244:Course: Data Center Scale Computing	10
fg-341:Course: Parallel Computing	6
fg-404:Enhancing Usage of cloud Infrastructure	6
fg-316:Course: Cloud Computing Class - third edition	6
fg-233:CINET - A Cyber-Infrastructure for Network Science	5
fg-364:Course: EEL6871 Autonomic Computing	5
fg-97:FutureGrid and Grid‘5000 Collaboration	4
fg-243:Applied Cyberinfrastructure concepts	3
fg-136:JGC-DataCloud-2012 paper experiments	3
fg-264:Course: 1st Workshop on bioKepler Tools and Its Applications	2
fg-340:Research: Parallel Computing for Machine Learning	1

Figure 7: VMs count by project leader

This chart also illustrates the proportion of launched VM instances by project Leader. The same data in tabular form follows.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

VMs count by project leader

Projectleader	Value
Gregor von Laszewski	1211
Shava Smallen	848
Randall Sobie	426
Lavanya Ramakrishnan	337
Theron Voran	219
Jan Balewski	218
Andy Li	168
Paolo Romano	158
Pierre Riteau	138
ibrahim hallac	108
Dirk Grunwald	64
Renato Figueiredo	60
Tirtha Bhattacharjee	56
John Lockman	40
Jonathan Klinginsmith	37
Shiyong Lu	31
Nirav Merchant	24
Thomas Fahringer	16
Philip Rhodes	15
Yong-Yeol Ahn	15
Carl Walasek	12
Wilson Rivera	7
Massimo Canonico	6
Rahul Limbole	6
Keith Bisset	5
Meng Han	5
Mauricio Tsugawa	4
Mats Rynge	3
Ilkay Altintas	2

Figure 8: VMs count by institution

This chart illustrates the proportion of launched VM instances by Institution. The same data in tabular form follows.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

VMs count by institution

Institution	Value
Indiana University	1263
UC San Diego	848
University of Victoria	426
Lawrence Berkeley National Lab	337
University of Colorado at Boulder, Computer Science Department	219
Massachusetts Institute of Technology, Laboratory for Nuclear Sc	218
University of Florida, Department of Electrical and Computer Eng	168
INESC ID	158
University of Chicago	138
Firat University, Computer Science Department	108
Virginia Bioinformatics Institute, Virginia Polytechnic Institut	56
Univ. of Colorado, Boulder, Computer Science	54
University of Florida	52
University of Texas at Austin	40
Wayne State University	31
University of Arizona, Arizona Research Laboratories, School of	21
University of Innsbruck	16
University of Mississippi, Department of Computer Science	15
University of Florida, Electrical and Computer Engineering	12
University of the Sciences , Mathematics, Physics, and Statistic	12
Univ. of Colorado	10
University of Puerto Rico, Electrical and Computer Emgineering D	7
Veermata Jijabai Technological Institute Mumbai, Computer Scienc	6
University of Piemonte Orientale, Computer Science Department	6
University of Florida, ACIS	5
Virginia Tech	5
USC	3
University of Arizona	3
UCSD	2

Figure 9: Wall time (hours) by project leader

This chart illustrates proportionate total run times by project leader.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

System information

System information shows utilization distribution as to VMs count and wall time. Each cluster represents a compute node.

Figure 10: VMs count by systems (compute nodes) in Cluster (sierra)

This column chart represents VMs count among systems.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra

Figure 11: Wall time (hours) by systems (compute nodes) in Cluster (sierra)

This column chart represents wall time among systems.

• Period: November 13 – May 13, 2014
• Cloud(IaaS): nimbus, openstack, eucalyptus
• Hostname: sierra