Architecture of Computing Systems (Lecture Notes in Computer ...

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168 M.F. Dolz et al. been submitted to each queue) and the users (as, e.g., the name, the user’s group, the number of jobs submitted to each queue by this user, and the average waiting and execution times of the jobs which have been submitted by this user). Finally, the database records a history of the actions in each node (activations/deactivations), the action timestamp, and the cause (e.g., if the node was deactivated because a certain condition was satisfied). 3.4 Website Interface The module has an interface that eases the administration of the energy saving module. Possible operations using this website include: – Check and modify configuration parameters of the energy saving system. – Look up, delete, and modify users’ groups in the system. – Look up and modify the parameters that define the activation/deactivation policies of each group of users. – Read the full database in HTML format, with the possibility to generate reports (as PDF documents) with the required information. – Monitor the operation of the cluster through a series of diagrams which illustrate the active/inactive node times, the average waiting time and execution time of jobs, etc. – Monitor the energy savings in terms of power consumption and economic cost. – Set “active” bits for those nodes that the administrator will always keep running, and declare unavailable nodes when they are crashed or being repaired. – Turn on, reset or shut down the three daemons, and reset counters and timers of the database. All changes done on the system configuration parameters are updated both in the database and the configuration files. Users without administrative privileges can only view reports, diagrams, and configuration parameters. 4 Experimental Results To evaluate the benefits of the system we have developed a flexible simulator, named EnergySaving-SIM, that provides information on the system behavior for various platform configurations and under realistic workloads. EnergySaving- SIM applies the desired activation and deactivation policies to a given input workload and can be easily adapted to reflect different types of platforms. Among many other statistics, the simulator reports the percentage of the time that each node in the cluster will be turned on/off and, therefore, offers an estimation of the energy consumption.
EnergySaving Cluster Roll: Power Saving System for Clusters 169 4.1 Implementation of EnergySaving-SIM The design of the EnergySaving-SIM consists of the following modules: – Queuing system: This module simulates a queuing system and submits, executes, and terminates jobs in a specified cluster according to the availability of the nodes (active or inactive) from an input workload. This workload can be obtained from a parsed log file resulting from a real queuing system that contains the time that a job was submitted, the execution time and its requirements (such as specific nodes, number of processors, etc.). This module provides the appropriate interfaces to interact with the energy saving module and uses a database to store the data of the jobs. – Energy saving: This module is the same used in the real system, but employs the interfaces provided by the queuing system module to check and query the status of jobs and make decisions to activate and deactivate nodes. By using the same code simulation we can obtain realistic simulations. – Results, statistics and graphs: When the simulation finishes, all the submit, start and finish times of jobs and activation/deactivation actions of nodes with its specific time are stored in the database. This application extracts various statistics such as total active and inactive time per node, job’s latency, etc. and prepares tables and graphs to evaluate energy consumption. 4.2 Simulation Results We have configured the simulator to emulate the system of queues of the HPC computing service at the Universidad Jaime I (UJI). This facility is composed of the following nodes: –Front-end: HP Proliant DL360 G5 with 2 dual core Intel Xeon 5160 processors, running at 3.00 GHz and with 14 GB of RAM. –Group1: 26 nodes, Fujitsu Siemens RX200 with 2 Intel Xeon processors running at 3.06 GHz and with 4 GB of RAM. –Group2: 27 nodes, HP Proliant DL360 G5 with 2 dual core Intel Xeon 5160 processors at 3.00 GHz, with 14 GB of RAM. –Group3: 11 nodes, HP Proliant BL460C with 2 Quadcore Intel Xeon E5450 processors at 3.00 GHz, with 32 GB of RAM. – Altix: An SGI Altix 3700 server with 48 Itanium2 processors at 1.5 GHz, with 96 GB of RAM. The job benchmark was obtained from the real queue system logs of the computing facility at UJI. This benchmark features the following properties: – Composed by 10,415 jobs corresponding to the load submitted to the HPC computing facilities during three full months of 2009: 99.87% of the jobs required one processor, 0.12% required four processors, and 0.01% required eight processors.
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Lecture Notes in Computer Science 5
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Volume Editors Christian Müller-Sc
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General Chair Organization Christia
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Organization IX Hartmut Schmeck Kar
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Abdullah, Tariq 174 Alima, Luc Onan
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