Trace analysis report LCG

This is the trace analysis report (generated by reportgen.py) for the LCG system. The trace data was taken from the filename anon_jobs.gwf, which contains job data obtained from Parallel Workloads Archive. Below is a summary of the contents of the trace data:

  • Date first entry: Sun Nov 20 01:00:05 2005
  • CPU time consumed by jobs: 53y 179d 7h 26m 46s
  • Number of sites in the system: -
  • Number of CPUs in the trace: 24,115
  • Number of jobs in the trace: 188041
  • Number of users in the trace: 216
  • Number of groups in the trace: 28

System-wide characteristics

System utilization

We define the overall system utilization as the ratio between the total CPU time consumed by users, and the total CPU time available to the users. We compute the total CPU time consumed by users as the sum of CPU time consumed by each job in the system; for failed jobs, only those that have effectively spent resource time are considered. We compute the total CPU time available as the number of CPUs multiplied by the duration of a fixed time interval, c.q. 10 minutes Below we show the statistical properties of both the overall system utilization and the overall system for non-zero values, that is, excluding all intervals that have system utilization equal to zero. This excludes values that may account for downtime of the system Unfortunately, utilization info for this trace is incomplete.

Job arrival rate

We define the job arrival rate as the number of jobs that are submitted to the system in a fixed time interval. We compute the arrival rate for every hour by counting the all jobs that are recorded in the trace during that hour. This includes failed jobs and jobs that are cancelled before execution. Below we list the time periods in which the highest number of jobs were submitted to the system. We also summarize statistical properties for all job arrival rate values, and the statistical properties for arrival rate higher than zero. This excludes time periods that may account to downtime of the system.

Figure 1 shows Overall job arrival rate during hourly intervals.

Figure 1: Overall job arrival rate during hourly intervals

Busiest time periods in terms of number of job submissions

  • Busiest day: 2005-11-30
  • Busiest week: 2005-47
  • Busiest month: 2005-11

Overall job arrival metrics

  • Minimum: 0.00 jobs/hour
  • Maximum: 1638.00 jobs/hour
  • Average: 504.13 jobs/hour

Overall job arrival metrics for non-zero values

  • Minimum: 191.00 jobs/hour
  • Maximum: 1638.00 jobs/hour
  • Average: 712.28 jobs/hour

Job characteristics

We compute three important characteristics of jobs in the trace: number of CPUs used, the runtime of the job and the amount of memory used. Below we summarize the statistical properties for single jobs in the trace. We do not include jobs that were cancelled before execution, because those jobs did not consume resources from the system.

Figure 2 shows CDFs of the most important job characteristics.

Figure 2: CDFs of the most important job characteristics

Number of CPUs used by a single job

  • Minimum: 1 processors
  • Maximum: 1 processors
  • Average: 1.000 processors
  • Standard deviation: 0.000
  • Coefficient of variation: 0.000

Runtime of a single job

  • Minimum: 0.00 seconds
  • Maximum: 586702.00 seconds
  • Average: 8970.92 seconds
  • Standard deviation: 32833.073
  • Coefficient of variation: 3.660

Memory usage of a single job

  • Minimum: 0.00 MB
  • Maximum: 0.00 MB
  • Average: 0.00 MB
  • Standard deviation: 0.000
  • Coefficient of variation: 0.000

Sequential vs. Parallel jobs

Below we summarize the resource usage of all sequential and all parallel jobs, that is all jobs that use more than one processor. First we calculate the number of sequential jobs and the number of parallel jobs that are submitted to the system. Furthermore, we compute the consumed CPU time by multiplying the runtime of a job by the number of processors allocated to the job. Again, this is divided into parallel and sequential jobs. For the number of jobs and the consumed CPU time, the percentage of all jobs is displayed.

Number of jobs

  • Sequential: 188041 jobs (100.00 percent)
  • Parallel: 0 jobs (0.00 percent)

Consumed CPU Time

  • Sequential: 1686900406 seconds (100.00 percent)
  • Parallel: 0 seconds (0.00 percent)

User and group characteristics

User characteristics

Figure 3 shows The number of submitted jobs and the consumed CPU time by user.

Figure 3: The number of submitted jobs (left) and consumed CPU time (right) by user. Only the top 10 users are displayed. The horizontal axis depicts the user's rank. The vertical axis shows the cumulated values, and the breakdown per week. Users have the same labels in the left and right sub-graphs

Top 10 users by number of job submitted to the system

Table 1 shows Top 10 users by number of jobs submitted to the system.

Table 1
Rank UserID Number of jobs Percentage
1 U1 60658 32.26%
2 U7 17697 9.41%
3 U15 13624 7.25%
4 U19 8449 4.49%
5 U14 5485 2.92%
6 U56 4842 2.57%
7 U5 4561 2.43%
8 U3 4138 2.20%
9 U2 3305 1.76%
10 U10 3071 1.63%
11 Other 62211 33.08%
12 Total 188041 100.00%

Job arrival

  • Minimum: 0.00 jobs/hour
  • Maximum: 1364.00 jobs/hour
  • Average: 353.46 jobs/hour

Job characteristics

Number of CPUs used by a single job

  • Minimum: 1 processors
  • Maximum: 1 processors
  • Average: 1.000 processors
  • Standard deviation: 0.000
  • Coefficient of variation: 0.000

Runtime of a single job

  • Minimum: 0.00 seconds
  • Maximum: 510461.00 seconds
  • Average: 4632.86 seconds
  • Standard deviation: 20573.538
  • Coefficient of variation: 4.441

Memory usage of a single job

  • Minimum: 0.00 MB
  • Maximum: 0.00 MB
  • Average: 0.00 MB
  • Standard deviation: 0.000
  • Coefficient of variation: 0.000

Top 10 users by consumed CPU time

Table 2 shows Top 10 users by consumed CPU time (in seconds).

Table 2
Rank UserID CPU seconds Percentage
1 U76 172627504 10.23%
2 U1 149877020 8.88%
3 U7 138988158 8.24%
4 U8 128555905 7.62%
5 U56 117455450 6.96%
6 U182 111812964 6.63%
7 U19 102949659 6.10%
8 U37 59967968 3.55%
9 U122 40729485 2.41%
10 U24 38974277 2.31%
11 Other 624962016 37.05%
12 Total 1686900406 100.00%

Job arrival

  • Minimum: 0.00 jobs/hour
  • Maximum: 989.00 jobs/hour
  • Average: 263.45 jobs/hour

Job characteristics

Number of CPUs used by a single job

  • Minimum: 1 processors
  • Maximum: 1 processors
  • Average: 1.000 processors
  • Standard deviation: 0.000
  • Coefficient of variation: 0.000

Runtime of a single job

  • Minimum: 0.00 seconds
  • Maximum: 586702.00 seconds
  • Average: 10806.55 seconds
  • Standard deviation: 40744.858
  • Coefficient of variation: 3.770

Memory usage of a single job

  • Minimum: 0.00 MB
  • Maximum: 0.00 MB
  • Average: 0.00 MB
  • Standard deviation: 0.000
  • Coefficient of variation: 0.000

Group characteristics

Figure 4 shows The number of submitted jobs and consumed CPU time by group.

Figure 4: The number of submitted jobs (left) and consumed CPU time (right) by group. Only the top 10 groups are displayed. The horizontal axis depicts the groups rank. The vertical axis shows the cumulated values, and the breakdown per week. Groups have the same labels in the left and right sub-graphs

Table 3 shows Top 10 groups by number of jobs submitted to the system.

Table 3
Rank GroupID Number of jobs Percentage
1 G1 68893 36.64%
2 G4 49292 26.21%
3 G6 25993 13.82%
4 G16 14372 7.64%
5 G2 8477 4.51%
6 G5 4563 2.43%
7 G3 4138 2.20%
8 G11 2983 1.59%
9 G13 2747 1.46%
10 G21 1932 1.03%
11 Other 4651 2.47%
12 Total 188041 100.00%

Table 4 shows Top 10 Groups by consumed CPU time (in seconds). 

Table 4
Rank GroupID CPU seconds Percentage
1 G4 1158510528 68.68%
2 G1 165866525 9.83%
3 G16 111702494 6.62%
4 G2 76666020 4.54%
5 G11 38642381 2.29%
6 G21 29891288 1.77%
7 G9 16373286 0.97%
8 G5 15863260 0.94%
9 G7 15149713 0.90%
10 G8 14161628 0.84%
11 Other 44073283 2.61%
12 Total 1686900406 100.00%

Performance analysis

Waiting and running jobs

Figure 5 shows The number of running and of waiting jobs during hourly intervals. The vertical axis is limited to 7500 for better visibility.

Figure 5: The number of running and of waiting jobs during hourly intervals. The vertical axis is limited to 7500 for better visibility

We compute the number of running and waiting jobs by considering a fixed time interval. In each time interval, we count in the trace the amount of jobs that have been submitted but not yet started, that is, waiting. We also count the number of jobs that have been submitted, and have started executing in the time interval, but did not finish executing, and thus are running. Below we show the values for an interval value of 3600 seconds, summarized in amounts per day. Also the summary for values higher than zero are displayed, which excludes the possible effect of downtime of the system.

Number of waiting jobs per day

  • Minimum: 0 jobs
  • Maximum: 0 jobs
  • Average: 0.00 jobs

Number of waiting jobs per day (non-zero values)

  • Minimum: 0 jobs
  • Maximum: 0 jobs
  • Average: 0.00 jobs

Number of running jobs per day

  • Minimum: 0 jobs
  • Maximum: 26243 jobs
  • Average: 13702.63 jobs

Number of running jobs per day (non-zero values)

  • Minimum: 24 jobs
  • Maximum: 26243 jobs
  • Average: 14616.13 jobs

Throughput

We compute the job throughput by considering a fixed time interval. In each time interval, we count in the trace the amount of jobs that have been submitted, started and finished executing. Below we show the values for an interval value of 3600 seconds, summarized in amounts per day. Also the summary for values higher than zero are displayed, which excludes the possible effect of downtime of the system.

Figure 6 shows Throughput during hourly intervals. The vertical axis of each individual site graph is limited to 7500 for better visibility..

Figure 6: Throughput during hourly intervals. The vertical axis of each individual site graph is limited to 7500 for better visibility

Throughput per day

  • Minimum: 0 jobs
  • Maximum: 21946 jobs
  • Average: 11752.06 jobs

Throughput per day (non-zero values)

  • Minimum: 16 jobs
  • Maximum: 21946 jobs
  • Average: 12535.53 jobs

Completed jobs

Figure 7 shows The number of completed jobs during hourly intervals.

Figure 7: The number of completed jobs during hourly intervals

Workload model

This section contains the workload model for the analyzed trace. The workload model consists of several parameters: job size, job runtime, requested runtime and interrarivals of jobs. These parameters are modeled by fitting well-known distributions to the data obtained from the trace. In all cases, first a logarithmic transformation was performed on the dataset to diminish the effect of outliers and speed up the modelling process. The fitting was performed using the maximum likelihood estimation method, which tries to maximize the log-likelihood function of each distribution given a dataset.

Job runtime

Figure 9 shows Cumulative distribution function for the logarithm of the job runtimes, with fitted distributions.

Figure 9: Cumulative distribution function for the logarithm of the job runtimes, with fitted distributions

Job interarrival

Figure 11 shows Cumulative distribution function for the logarithm of the job interarrival, with fitted distributions.

Figure 11: Cumulative distribution function for the logarithm of the job interarrival, with fitted distributions

Side content