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

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170 M.F. Dolz et al. On the other hand, 73.3% of the jobs was executed on group 1, 0% requested group 2, 16.99% requested group 3, and 9.7% requested the Altix server. – The average execution time of the jobs was 1 day, 2 hours and 53 minutes. We evaluated the following policies: – No Policy (NP): This configuration represents a conventional cluster without the energy saving module on which nodes are permanently active. – Policy 1 (P1): • Activation/deactivation conditions: 1. Job without resources (Turn on). 2. Idle time of a node (Turn off): Max. idle time: 60 seconds. • Node selection algorithm: Ordered. • Strict level: No strict. – Policy 2 (P2): This is the same configuration as P1, except for the Strict level which is changed from “No strict” to “Strict” level. – Policy 3 (P3): This is the same configuration as P1, except for the Strict level which is changed from “No strict” to “Strict and sequential” level. Table 1 reports the following results obtained with the simulator: –Latency: Average time since jobs are submitted till their execution is completed. This value thus includes the time a job is enqueued as well as its execution time. – Power on time (%): Average fraction of the total time that the nodes of the cluster remain turned on. –Totaltime: Elapsed time since the first job is submitted till the last job completes its execution. – Total consumption: Total consumption in MWatts-hour (MWh). (We have considered that a node consumes on average 250 Watts/hour.) The results in the table show that the NP policy, where all the nodes are powered on all the time, yields an average response time (latency) per job over 339 h, and consumes consumes 65.37 MWh to execute the 10,415 jobs. The application of policy P1 (“No strict” level) roughly increases the job latency to 461 h, but now the percentage of time that nodes are powered on is only 42.9%, and the power consumption is reduced to 29.51 MWh. Table 1. Execution time and energy savings obtained for different policies Policy Latency Power on Total time Total time consumption NP 339 h, 44 m, 18 s 100.0% 4,022 h, 39 m, 50 s 65.37 P1 461 h, 54 m, 0 s 42.9% 4,022 h, 49 m, 15 s 29.51 P2 12,387 h, 56 m, 34 s 5.8% 29,962 h, 2 m, 41 s 46.50 P3 36,556 h, 28 m, 9 s 2.2% 86,712 h, 51 m, 31 s 85.73
EnergySaving Cluster Roll: Power Saving System for Clusters 171 Policy P2 produces worse results than P1. As most of the jobs require a single processor, with the “Strict” level new nodes are not turned on until a job requests more processors. Thus, when most jobs require the same number of nodes, this is basically equivalent to a sequential execution. In particular, the job latency is increased to more than 12,387 h, the time the nodes are active is reduced to only 5.8%, and the time to complete the benchmark is now close to 30,000 h; moreover, the power consumption is increased to 46.50 MWh. In summary, this policy is not appropriate for this type of jobs, though it can be potentially interesting in other cases; e.g., when the batch of jobs requests very different number of processors. Policy P3 presents a long response time, and although the consumption is reduced to only 2.2%, the time to complete the benchmark raises to almost 86,713 h. Interestingly, the power consumption of this policy exceeds that of NP. Policy P3 is more restrictive than P2, because it uses the “Strict and sequential” level, and therefore, no inactive nodes are powered on until all processors in turned on nodes are idle. For this particular benchmark, this policy is not appropriate. However, as was the case with policy P2, P3 can deliver better best results in case the jobs request multiple processors. We will only discuss policy P1 hereafter, as policies P2 and P3 were not competitive for this workload. Table 2 reports more detailed results for P1. The first row in the table shows the number of node shut-downs happened in about 4,000 h: 206 shutdowns for a 65-node cluster is a reduced number. This means that, in average, a node was activated and deactivated slightly more than 3 times in 4,000 h. The largest number of active nodes at any given moment is 37 (out of 65), with the reason for this being that no job of the workload required nodes of group 2. The following rows show the active and inactive average time for all nodes in the cluster. To obtain these metrics, we collected the active and inactive time per node to calculate the total average. This metric illustrates the time that the nodes are powered on: basically 1,723 h of a total of 4,000 h, or 42.9% of the time. The last two rows of results in the table display the total active/inactive average time of nodes from the local averages of active and inactive intervals per node. Looking Table 2. Detailed results for policy P1 Measure Total Per node Number of shutdowns 206 3.17 Maximum active nodes 37 of 65 - Minimum active nodes 1of65 - Active time 112,056 h, 24 m, 28 s 1,723 h, 56 m, 41 s Inactive time Active time with average 149,424 h, 46 m, 47 s 2,298 h, 50 m, 33 s of active intervals per node Inactive time with average 25,462 h, 29 m, 0 s 391 h, 43 m, 49 s of inactive intervals per node 120,678 h, 57 m, 53 s 1,856 h, 35 m, 58 s
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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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Keynote Table of Contents HyVM - Hy
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Table of Contents XIII JetBench:AnO
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How to Enhance a Superscalar Proces
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4 J. Mische et al. The Real-time Vi
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Abdullah, Tariq 174 Alima, Luc Onan
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