using schedflow for performance evaluation of workflow applications
DESCRIPTION
Using SchedFlow for Performance Evaluation of Workflow Applications. Elisa Heyman Gustavo Martínez Miquel Angel Senar Emilio Luque Universitat Aut ònoma de Barcelona [email protected]. Barton P. Miller University of Wisconsin [email protected]. 1. T1. T2. T3. T4. T5. - PowerPoint PPT PresentationTRANSCRIPT
![Page 1: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/1.jpg)
1
Using SchedFlow for Performance Evaluation of Workflow Applications
Barton P. Miller
University of Wisconsin
Elisa HeymanGustavo Martínez
Miquel Angel Senar Emilio Luque
Universitat Autònoma de Barcelona
![Page 2: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/2.jpg)
2
Our Problem
T1
T2 T3
T4 T5 T6
T7
Scheduling Policies
Workflow Engines
![Page 3: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/3.jpg)
3
Our Solution
T1
T2 T3
T4 T5 T6
T7
Scheduling Policies
Workflow Engines
SchedFlow
![Page 4: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/4.jpg)
4
Outline› Introduction› SchedFlow› Experimental Study› Conclusions
![Page 5: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/5.jpg)
5
Introduction› For executing a workflow on a
distributed environment, we need:› Scheduling policy integrated into a› Workflow engine
› Reduce makespan› Factors
› Workload size› Inaccurate computing and
communication times› Machines appearing/disappering
dynamically
![Page 6: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/6.jpg)
6
Introduction› With SchedFlow, we assessed the
influence of the workload on the makespan considering:› Different scheduling policies › Different workflow engines
![Page 7: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/7.jpg)
SchedFlowT1
T2 T3
T4 T5 T6
T7
User PolicyAPI
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 8: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/8.jpg)
T1
T2 T3
T4
The user submits a workflow
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
User PolicyAPI
![Page 9: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/9.jpg)
T1
T2
T3
The Scheduler uses the specified scheduling policy on the available resources discovered by the Observer.
M1
M2
M3
T4 M4
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 10: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/10.jpg)
T1
T2
T3
The Controller receives the first task-machine pairs
M2
M3
T4 M4
M1
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 11: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/11.jpg)
T1
T2
T3
The Controller tells the adaptor which engine to use. The adaptor deals with formatting and enqueues the task.
M2
M3
T4 M4
M1
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 12: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/12.jpg)
T2
T3
M2
M3
T4 M4
M1
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logsT1
![Page 13: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/13.jpg)
T2
T3
The Engine sends the task to the assigned machine. The Observer checks the Engine log for finished tasks.
M2
M3
T4 M4
SchedFlow
M1T1
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 14: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/14.jpg)
T2
T3
When the task finishes, the Observer notifies the Scheduler.
M2
M3
T4 M4
SchedFlow
M1
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 15: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/15.jpg)
T2 T3
T4 M4
The Scheduler finds the tasks that have their dependencies satisfied and sends them to the Controller.
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
![Page 16: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/16.jpg)
T2 T3
T4 M4
M2
M3
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 17: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/17.jpg)
T4 M4
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
T2 T3
![Page 18: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/18.jpg)
T4 M4
M2
M3
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
T2
T3
![Page 19: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/19.jpg)
T2 finishes OK.M3 is claimed.
T4 M4
M2
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3T3
![Page 20: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/20.jpg)
The Observer detects the problem and T3 is removed from M3 and dynamcally rescheduled.
T4 M4
M2
M3
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3T3
![Page 21: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/21.jpg)
T3 is rescheduled. The Observer does not include M3 as an available resource.
T4 M4
T3
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
![Page 22: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/22.jpg)
T4 M4
T3 M2
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
![Page 23: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/23.jpg)
T4 M4
T3
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
![Page 24: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/24.jpg)
T4 M4
T3
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
![Page 25: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/25.jpg)
T4 M4
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
T3
![Page 26: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/26.jpg)
T4 M4
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
T3
![Page 27: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/27.jpg)
T4 M4
T3 finishes OK. The Observer notifies the Scheduler, and it releases T4.
SchedFlow
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
M2
M3
![Page 28: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/28.jpg)
T4
SchedFlow
M4
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 29: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/29.jpg)
T4
SchedFlow
M4
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
![Page 30: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/30.jpg)
SchedFlow
M4
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logsT4
![Page 31: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/31.jpg)
SchedFlow
M4
queue
Task manager
Controller Observer
SchedulerScheduler
SchedulerScheduler
Adaptor
Scheduler
Adaptor
Workflow Engine
logs
T4
When T4 finishes the Observer computes the makespan.
![Page 32: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/32.jpg)
32
Experimental Study› Execution environment:
– 140 machines› Workflow applications:
– Montage (53 tasks) – LIGO (81 tasks)
› Workflow engines:– Condor-DAGMan 7.0– Taverna 1.4.8– Karajan 4_0_a1
![Page 33: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/33.jpg)
33
Experimental Study› Scheduling policies:
– Default– Min-min– HEFT– BMCT
![Page 34: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/34.jpg)
34
Experimental Study› Input workload:
– 400 MB– 1024 MB
› We studied the effect of the scheduling policies.
› We measured application makespan› Real executions
![Page 35: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/35.jpg)
35
Results› Mantage ran on Taverna, DAGMan,
Karajan› 400 MB input workload› 120 executions› Default scheduling policy
Taverna DAGMan Karajan0
2000
4000
6000
8000
10000
12000
14000
Worflow engine with default Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 36: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/36.jpg)
36
Results› Same experiments but using SchedFlow› Min-min, HEFT, BMCT› Rescheduling
Taverna DAGMan Karajan0
2000
4000
6000
8000
10000
12000
14000
Default min-min HEFT BMCT
Worflow engine with differents Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 37: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/37.jpg)
37
Results› Mantage ran on Taverna, DAGMan,
Karajan› 1024 MB input workload› 120 executions› Default scheduling policy
Taverna DAGMan Karajan0
4000
8000
12000
16000
20000
24000
28000
Worflow engine with default Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 38: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/38.jpg)
38
Results› Same experiments but using SchedFlow› Min-min, HEFT, BMCT› Rescheduling
Taverna DAGMan Karajan0
4000
8000
12000
16000
20000
24000
28000
Default min-min HEFT BMCT
Worflow engine with differents Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 39: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/39.jpg)
39
Results› LIGO ran on Taverna, DAGMan, Karajan› 400 MB input workload› 120 executions› Default scheduling policy
Taverna DAGMan Karajan0
4000
8000
12000
16000
20000
24000
28000
Worflow engine with default Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 40: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/40.jpg)
40
Results› Same experiments but using SchedFlow› Min-min, HEFT, BMCT› Rescheduling
Taverna DAGMan Karajan0
4000
8000
12000
16000
20000
24000
28000
Default min-min HEFT BMCT
Worflow engine with differents Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 41: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/41.jpg)
41
Results› LIGO ran on Taverna, DAGMan, Karajan› 1024 MB input workload› 120 executions› Default scheduling policy
Taverna DAGMan Karajan0
10000
20000
30000
40000
50000
60000
Worflow engine with default Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 42: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/42.jpg)
42
Results› Same experiments but using SchedFlow› Min-min, HEFT, BMCT› Rescheduling
Taverna DAGMan Karajan0
10000
20000
30000
40000
50000
60000
Default min-min HEFT BMCT
Worflow engine with differents Scheduling Policies
Mak
espa
n av
erag
e (s
ec.)
![Page 43: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/43.jpg)
43
Conclusions› No single scheduling policy is the best for
all scenarios› SchedFlow allows us to obtain better
performance providing:– Flexibility regarding scheduling policies– Support for rescheduling– Integration with Workflow Engines
![Page 44: Using SchedFlow for Performance Evaluation of Workflow Applications](https://reader035.vdocument.in/reader035/viewer/2022081513/56816178550346895dd10667/html5/thumbnails/44.jpg)
44
Using SchedFlow for Performance Evaluation of Workflow Applications
Barton P. Miller
University of Wisconsin
Elisa HeymanGustavo Martínez
Miquel Angel Senar Emilio Luque
Universitat Autònoma de Barcelona