Usage Report hotel

• Period: December 01 – December 23, 2013
• Hostname: hotel.futuregrid.org
• Services: nimbus
• 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: December 01 – December 23, 2013

• Cloud(IaaS): nimbus

• Hostname: hotel

• 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: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

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: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

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: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

Distribution

Figure 5: VM count by wall time

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

• Period: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

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: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

VMs count by project

Project	Value
fg-82:FG General Software Development	138
fg-224:Nimbus Auto Scale	47
fg-54:Investigating cloud computing as a solution for analyzing particle physics data	32
fg-364:Course: EEL6871 Autonomic Computing	22
fg-213:Course: Cloud Computing class - second edition	7
fg-340:Research: Parallel Computing for Machine Learning	6
fg-362:Course: Cloud Computing and Storage (UF)	5
fg-371:Characterizing Infrastructure Cloud Performance for Scientific Computing	3
fg-391:Topics in Parallel Computation	2
fg-201:ExTENCI Testing, Validation, and Performance	1
fg-97:FutureGrid and Grid‘5000 Collaboration	1
fg-10:TeraGrid XD TIS(Technology Insertion Service) Technology Evaluation Laboratory	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: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

VMs count by project leader

Projectleader	Value
Gregor von Laszewski	138
Pierre Riteau	47
Randall Sobie	32
Meng Han	22
Massimo Canonico	7
Wilson Rivera	6
Andy Li	5
Theron Voran	3
Heru Suhartanto	2
Mauricio Tsugawa	1
John Lockman	1
Preston Smith	1

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: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

VMs count by institution

Institution	Value
Indiana University	138
University of Chicago	47
University of Victoria	32
University of Florida, ACIS	22
University of Piemonte Orientale	7
University of Puerto Rico, Electrical and Computer Emgineering D	6
University of Florida, Department of Electrical and Computer Eng	5
University of Colorado at Boulder, Computer Science Department	3
Universitas Indonesia, Faculty of Computer Science	2
University of Texas at Austin	1
Purdue University	1
University of Florida	1

Figure 9: Wall time (hours) by project leader

This chart illustrates proportionate total run times by project leader.

• Period: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

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 (hotel)

This column chart represents VMs count among systems.

• Period: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel

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

This column chart represents wall time among systems.

• Period: December 01 – December 23, 2013
• Cloud(IaaS): nimbus
• Hostname: hotel