Using Condor
An Introduction
ICE 2010
http://www.cs.wisc.edu/condor
1
The Condor Project
(Established ‘85)
Distributed
High
Throughput
Computing
research
performed by
a team of ~35
faculty, full
time staff and
students.
http://www.cs.wisc.edu/condor
2
Definitions
› Job
The Condor representation of your work
› Machine
The Condor representation of computers
and that can perform the work
› Match Making
Matching a job with a machine “Resource”
http://www.cs.wisc.edu/condor
3
Job
Jobs state their requirements and
preferences:
I need a Linux/x86 platform
I need the machine at least 500 Mb
I prefer a machine with more memory
http://www.cs.wisc.edu/condor
4
Machine
Machines state their requirements and
preferences:
Run jobs only when there is no keyboard
activity
I prefer to run Frieda’s jobs
I am a machine in the econ department
Never run jobs belonging to Dr. Smith
http://www.cs.wisc.edu/condor
5
The Magic of Matchmaking
› Jobs and machines state their
requirements and preferences
› Condor matches jobs with machines
based on requirements and preferences
http://www.cs.wisc.edu/condor
6
Getting Started:
Submitting Jobs to Condor
› Overview:
Choose a “Universe” for your job
Make your job “batch-ready”
Create a submit description file
Run condor_submit to put your job in the
queue
http://www.cs.wisc.edu/condor
7
1. Choose the “Universe”
› Controls how Condor handles jobs
› Choices include:
Vanilla
Standard
Grid
Java
Parallel
VM
http://www.cs.wisc.edu/condor
8
Using the Vanilla Universe
• The Vanilla Universe:
– Allows running almost
any “serial” job
– Provides automatic file
transfer, etc.
– Like vanilla ice cream
• Can be used in just
about any situation
http://www.cs.wisc.edu/condor
9
2. Make your job batchready
Must be able to run in
the background
• No interactive input
• No GUI/window
clicks
• No music ;^)
http://www.cs.wisc.edu/condor
10
Make your job batch-ready
(continued)…
Job can still use STDIN, STDOUT, and
STDERR (the keyboard and the screen),
but files are used for these instead of
the actual devices
Similar to UNIX shell:
• $ ./myprogram <input.txt >output.txt
http://www.cs.wisc.edu/condor
11
3. Create a Submit
Description File
› A plain ASCII text file
› Condor does not care about file extensions
› Tells Condor about your job:
Which executable, universe, input, output and error
files to use, command-line arguments, environment
variables, any special requirements or preferences
(more on this later)
› Can describe many jobs at once (a “cluster”),
each with different input, arguments, output,
etc.
http://www.cs.wisc.edu/condor
12
Simple Submit Description
File
# Simple condor_submit input file
# (Lines beginning with # are comments)
# NOTE: the words on the left side are not
#
case sensitive, but filenames are!
Universe
= vanilla
Executable = my_job
Output
= output.txt
Queue
http://www.cs.wisc.edu/condor
13
4. Run condor_submit
› You give condor_submit the name of
the submit file you have created:
condor_submit my_job.submit
› condor_submit:
Parses the submit file, checks for errors
Creates a “ClassAd” that describes your
job(s)
Puts job(s) in the Job Queue
http://www.cs.wisc.edu/condor
14
The Job Queue
› condor_submit sends your job’s
ClassAd(s) to the schedd
› The schedd (more details later):
Manages the local job queue
Stores the job in the job queue
• Atomic operation, two-phase commit
• “Like money in the bank”
› View the queue with condor_q
http://www.cs.wisc.edu/condor
15
Example
condor_submit and condor_q
% condor_submit my_job.submit
Submitting job(s).
1 job(s) submitted to cluster 1.
% condor_q
-- Submitter: perdita.cs.wisc.edu : <128.105.165.34:1027> :
ID
OWNER
SUBMITTED
RUN_TIME ST PRI SIZE CMD
1.0
frieda
6/16 06:52
0+00:00:00 I 0
0.0 my_job
1 jobs; 1 idle, 0 running, 0 held
%
http://www.cs.wisc.edu/condor
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Input, output & error files
› Controlled by submit file settings
› You can define the job’s standard input,
standard output and standard error:
Read job’s standard input from “input_file”:
• Input = input_file
• Shell equivalent: program <input_file
Write job’s standard ouput to “output_file”:
• Output = output_file
• Shell equivalent: program >output_file
Write job’s standard error to “error_file”:
• Error = error_file
• Shell equivalent: program 2>error_file
http://www.cs.wisc.edu/condor
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Email about your job
• Condor sends email about job
events to the submitting user
• Specify “notification” in your
submit file to control which
events:
Notification
Notification
Notification
Notification
=
=
=
=
complete
never
error
always
Default
http://www.cs.wisc.edu/condor
18
Feedback on your job
› Create a log of job events
› Add to submit description file:
log = sim.log
› Becomes the Life Story of a Job
Shows all events in the life of a job
Always have a log file
http://www.cs.wisc.edu/condor
19
Sample Condor User Log
000 (0001.000.000) 05/25 19:10:03 Job submitted from host:
<128.105.146.14:1816>
...
001 (0001.000.000) 05/25 19:12:17 Job executing on host:
<128.105.146.14:1026>
...
005 (0001.000.000) 05/25 19:13:06 Job terminated.
(1) Normal termination (return value 0)
...
http://www.cs.wisc.edu/condor
20
Example Submit Description
File With Logging
# Example condor_submit input file
# (Lines beginning with # are comments)
# NOTE: the words on the left side are not
#
case sensitive, but filenames are!
Universe
= vanilla
Executable = /home/frieda/condor/my_job.condor
Log
= my_job.log
·Job log (from Condor)
Input
= my_job.in
·Program’s standard input
Output
= my_job.out
·Program’s standard output
Error
= my_job.err
·Program’s standard error
Arguments = -a1 -a2
·Command line arguments
InitialDir = /home/frieda/condor/run
Queue
http://www.cs.wisc.edu/condor
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Let’s run a job
› First, need a terminal emulator
http://www.putty.org
• (or similar)
› Login to chopin.cs.wisc.edu as
cguserXX, and the given password
http://www.cs.wisc.edu/condor
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Logged In?
› condor_q
› condor_status
http://www.cs.wisc.edu/condor
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Create submit file
› nano submit.your_initials
•
•
•
•
•
•
universe = vanilla
executable = /bin/echo
Arguments = hello world
Output = out
Log = log
queue
http://www.cs.wisc.edu/condor
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And submit it…
› condor_submit submit.your_initials
› (wait… remember the HTC bit?)
› Condor_q xx
› cat output
http://www.cs.wisc.edu/condor
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“Clusters” and “Processes”
› If your submit file describes multiple jobs, we call
›
›
›
this a “cluster”
Each cluster has a unique “cluster number”
Each job in a cluster is called a “process”
 Process numbers always start at zero
A Condor “Job ID” is the cluster number, a period,
and the process number (i.e. 2.1)
 A cluster can have a single process
• Job ID = 20.0
·Cluster 20, process 0
 Or, a cluster can have more than one process
• Job ID: 21.0, 21.1, 21.2
·Cluster 21, process 0, 1, 2
http://www.cs.wisc.edu/condor
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Submit
File
for
a
Cluster
# Example submit file for a cluster of 2 jobs
# with separate input, output, error and log files
Universe
= vanilla
Executable = my_job
Arguments = -x 0
log
= my_job_0.log
Input
= my_job_0.in
Output
= my_job_0.out
Error
= my_job_0.err
Queue
·Job 2.0 (cluster 2, process 0)
Arguments = -x 1
log
Input
Output
Error
Queue
=
=
=
=
my_job_1.log
my_job_1.in
my_job_1.out
my_job_1.err
·Job 2.1 (cluster 2, process 1)
http://www.cs.wisc.edu/condor
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Submitting The Job
% condor_submit my_job.submit-file
Submitting job(s).
2 job(s) submitted to cluster 2.
% condor_q
-- Submitter: perdita.cs.wisc.edu : <128.105.165.34:1027> :
ID
OWNER
SUBMITTED
RUN_TIME ST PRI SIZE CMD
1.0
frieda
4/15 06:52
0+00:02:11 R
0
0.0
my_job –a1 –a2
2.0
frieda
4/15 06:56
0+00:00:00 I
0
0.0
my_job –x 0
2.1
frieda
4/15 06:56
0+00:00:00 I
0
0.0
my_job –x 1
3 jobs; 2 idle, 1 running, 0 held
%
http://www.cs.wisc.edu/condor
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Organize your files and
directories for big runs
› Create subdirectories for each “run”
run_0, run_1, … run_599
› Create input files in each of these
run_0/simulation.in
run_1/simulation.in
…
run_599/simulation.in
› The output, error & log files for each job
will be created by Condor from your job’s
output
http://www.cs.wisc.edu/condor
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Submit Description File for
600 Jobs
# Cluster of
Universe
=
Executable =
Log
=
...
Arguments =
InitialDir =
Queue
600 jobs with different directories
vanilla
sim
simulation.log
-x 0
run_0
Arguments = -x 1
InitialDir = run_1
Queue
·Log, input, output & error files -> run_0
·Job 3.0 (Cluster 3, Process 0)
·Log, input, output & error files -> run_1
·Job 3.1 (Cluster 3, Process 1)
·Do this 598 more times…………
http://www.cs.wisc.edu/condor
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Submit File for a Big Cluster
of Jobs
› We just submitted 1 cluster with 600
processes
› All the input/output files will be in
different directories
› The submit file is pretty unwieldy (over
1200 lines)
› Isn’t there a better way?
http://www.cs.wisc.edu/condor
31
Submit File for a Big Cluster
of Jobs (the better way) #1
› We can queue all 600 in 1 “Queue”
command
Queue 600
› Condor provides $(Process) and
$(Cluster)
$(Process) will be expanded to the
process number for each job in the cluster
• 0, 1, … 599
$(Cluster) will be expanded to the
cluster number
• Will be 4 for all jobs in this cluster
http://www.cs.wisc.edu/condor
32
Submit File for a Big Cluster
of Jobs (the better way) #2
› The initial directory for each job can
be specified using $(Process)
InitialDir = run_$(Process)
Condor will expand these to “run_0”,
“run_1”, … “run_599” directories
› Similarly, arguments can be variable
Arguments = -x $(Process)
Condor will expand these to “-x 0”,
“-x 1”, … “-x 599”
http://www.cs.wisc.edu/condor
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Better Submit File for 600
Jobs
# Example condor_submit input file that defines
# a cluster of 600 jobs with different directories
Universe
= vanilla
Executable = my_job
Log
= my_job.log
Input
= my_job.in
Output
= my_job.out
Error
= my_job.err
Arguments = –x $(Process)
·–x 0, -x 1, … -x 599
InitialDir = run_$(Process)
·run_0 … run_599
Queue 600
·Jobs 4.0 … 4.599
http://www.cs.wisc.edu/condor
34
Now, we submit it…
$ condor_submit my_job.submit
Submitting job(s)
......................................................
......................................................
......................................................
......................................................
.......................................
Logging submit event(s)
......................................................
......................................................
......................................................
......................................................
.......................................
600 job(s) submitted to cluster 4.
http://www.cs.wisc.edu/condor
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And, Check the queue
$ condor_q
-- Submitter:
ID
OWNER
4.0
frieda
4.1
frieda
4.2
frieda
4.3
frieda
...
4.598 frieda
4.599 frieda
x.cs.wisc.edu : <128.105.121.53:510> : x.cs.wisc.edu
SUBMITTED
RUN_TIME ST PRI SIZE CMD
4/20 12:08 0+00:00:05 R 0
9.8 my_job -arg1 –x 0
4/20 12:08 0+00:00:03 I 0
9.8 my_job -arg1 –x 1
4/20 12:08 0+00:00:01 I 0
9.8 my_job -arg1 –x 2
4/20 12:08 0+00:00:00 I 0
9.8 my_job -arg1 –x 3
4/20 12:08 0+00:00:00 I
4/20 12:08 0+00:00:00 I
0
0
9.8
9.8
my_job -arg1 –x 598
my_job -arg1 –x 599
600 jobs; 599 idle, 1 running, 0 held
http://www.cs.wisc.edu/condor
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Removing jobs
› If you want to remove a job from the
Condor queue, you use condor_rm
› You can only remove jobs that you
own
› Privileged user can remove any jobs
“root” on UNIX
“administrator” on Windows
http://www.cs.wisc.edu/condor
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Removing jobs (continued)
› Remove an entire cluster:
condor_rm 4
·Removes the whole cluster
› Remove a specific job from a cluster:
condor_rm 4.0 ·Removes a single job
› Or, remove all of your jobs with “-a”
condor_rm -a
·Removes all jobs / clusters
http://www.cs.wisc.edu/condor
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Submit cluster of 10 jobs
› nano submit
•
•
•
•
•
•
universe = vanilla
executable = /bin/echo
Arguments = hello world $(PROCESS)
Output = out.$(PROCESS)
Log = log
Queue 10
http://www.cs.wisc.edu/condor
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And submit it…
› condor_submit submit
›
›
›
›
(wait…)
Condor_q xx
cat log
cat output.yy
http://www.cs.wisc.edu/condor
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My new jobs run for 20
days…
› What happens when a job is
forced off it’s CPU?
 Preempted by higher priority
user or job
Vacated because of user activity
› How can I add fault tolerance
to my jobs?
http://www.cs.wisc.edu/condor
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Condor’s Standard Universe
to the rescue!
› Support for transparent process
checkpoint and restart
› Remote system calls (remote I/O)
Your job can read / write files
as if they were local
http://www.cs.wisc.edu/condor
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Remote System Calls in
the Standard Universe
› I/O system calls are trapped and sent back
to the submit machine
Examples: open a file, write to a file
› No source code changes typically required
› Programming language independent
http://www.cs.wisc.edu/condor
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Process Checkpointing in the
Standard Universe
› Condor’s process checkpointing provides a
›
mechanism to automatically save the
state of a job
The process can then be restarted from
right where it was checkpointed
After preemption, crash, etc.
http://www.cs.wisc.edu/condor
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Checkpointing:
Process Starts
checkpoint: the entire state of a program,
saved in a file
 CPU registers, memory image, I/O
time
http://www.cs.wisc.edu/condor
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Checkpointing:
Process Checkpointed
time
1
2
3
http://www.cs.wisc.edu/condor
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Checkpointing:
Process Killed
time
Killed!
3
3
http://www.cs.wisc.edu/condor
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Checkpointing:
Process Resumed
goodput
badput
time
goodput
3
3
http://www.cs.wisc.edu/condor
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When will Condor
checkpoint your job?
› Periodically, if desired
For fault tolerance
› When your job is preempted by a higher
›
›
priority job
When your job is vacated because the
execution machine becomes busy
When you explicitly run condor_checkpoint,
condor_vacate, condor_off or
condor_restart command
http://www.cs.wisc.edu/condor
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Making the Standard
Universe Work
› The job must be relinked with Condor’s
›
standard universe support library
To relink, place condor_compile in front of
the command used to link the job:
% condor_compile gcc -o myjob myjob.c
- OR % condor_compile f77 -o myjob filea.f fileb.f
- OR -
% condor_compile make –f MyMakefile
http://www.cs.wisc.edu/condor
50
Limitations of the
Standard Universe
› Condor’s checkpointing is not at the kernel
level.
Standard Universe the job may not:
• Fork()
• Use kernel threads
• Use some forms of IPC, such as pipes and shared
memory
› Must have access to source code to relink
› Many typical scientific jobs are OK
http://www.cs.wisc.edu/condor
51
Submitting Std uni job
› #include <stdio.h>
› int main(int argc, char **argv) {
› int i;
for(i = 0 ; i < 10000000; i++) {
}
›}
http://www.cs.wisc.edu/condor
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And submit…
› condor_compile gcc –o foo foo.c
-- Change "vanilla" to "standard"
-- Change "/bin/echo" to "foo" (or above)
http://www.cs.wisc.edu/condor
53
My jobs have have
dependencies…
Can Condor help solve my
dependency problems?
http://www.cs.wisc.edu/condor
54
Condor Universes:
Scheduler and Local
› Scheduler Universe
Plug in a meta-scheduler
Developed for DAGMan (more later)
Similar to Globus’s fork job manager
› Local
Very similar to vanilla, but jobs run on
the local host
Has more control over jobs than
scheduler universe
http://www.cs.wisc.edu/condor
55
DAGMan
› Directed Acyclic Graph Manager
› DAGMan allows you to specify the
dependencies between your Condor jobs, so
it can manage them automatically for you.
› (e.g., “Don’t run job “B” until job “A” has
completed successfully.”)
http://www.cs.wisc.edu/condor
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What is a DAG?
› A DAG is the data structure
Job
A
used by DAGMan to represent
these dependencies.
› Each job is a “node” in the
DAG.
› Each node can have any
number of “parent” or
“children” nodes – as long as
there are no loops!
Job
B
Job
C
Job
D
http://www.cs.wisc.edu/condor
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Defining a DAG
› A DAG is defined by a .dag file, listing each of its
nodes and their dependencies:
# diamond.dag
Job A a.sub
Job B b.sub
Job C c.sub
Job D d.sub
Parent A Child B C
Parent B C Child D
Job A
Job B
Job C
Job D
› each node will run the Condor job specified by its
accompanying Condor submit file
http://www.cs.wisc.edu/condor
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Submitting a DAG
› To start your DAG, just run
condor_submit_dag with your .dag file,
and Condor will start a personal DAGMan
daemon which to begin running your jobs:
% condor_submit_dag diamond.dag
› condor_submit_dag is run by the schedd
DAGMan daemon itself is “watched” by Condor,
so you don’t have to
http://www.cs.wisc.edu/condor
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Running a DAG
› DAGMan acts as a “meta-scheduler”,
managing the submission of your jobs to
Condor based on the DAG dependencies.
A
Condor A
Job
Queue
B
C
.dag
File
DAGMan D
http://www.cs.wisc.edu/condor
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Running a DAG (cont’d)
› DAGMan holds & submits jobs to the
Condor queue at the appropriate times.
A
Condor B
Job
Queue C
B
C
DAGMan D
http://www.cs.wisc.edu/condor
61
Running a DAG (cont’d)
› In case of a job failure, DAGMan continues until it
can no longer make progress, and then creates a
“rescue” file with the current state of the DAG.
A
Condor
Job
Queue
B
X
DAGMan D
http://www.cs.wisc.edu/condor
Rescue
File
62
Recovering a DAG
› Once the failed job is ready to be re-run,
the rescue file can be used to restore the
prior state of the DAG.
A
Condor
Job
Queue C
B
C
Rescue
File
DAGMan D
http://www.cs.wisc.edu/condor
63
Recovering a DAG (cont’d)
› Once that job completes, DAGMan will
continue the DAG as if the failure never
happened.
A
Condor
Job
Queue D
B
C
DAGMan D
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64
Finishing a DAG
› Once the DAG is complete, the DAGMan
job itself is finished, and exits.
A
Condor
Job
Queue
B
C
DAGMan D
http://www.cs.wisc.edu/condor
65
Additional DAGMan
Features
› Provides other handy features
for job management…
nodes can have PRE & POST scripts
failed nodes can be automatically re-
tried a configurable number of times
job submission can be “throttled”
http://www.cs.wisc.edu/condor
66
What about Licensed Jobs?
› e.g. matlab
Site license?
matlab compiler
Octave
http://www.cs.wisc.edu/condor
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Chirp
› condor_chirp get_file remote local
› condor_chirp put_file local remote
http://www.cs.wisc.edu/condor
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›
›
›
›
›
›
›
›
›
General User Commands
condor_status
condor_q
condor_submit
condor_rm
condor_prio
condor_history
condor_submit_dag
condor_checkpoint
condor_compile
View Pool Status
View Job Queue
Submit new Jobs
Remove Jobs
Intra-User Prios
Completed Job Info
Submit new DAG
Force a checkpoint
Link Condor library
http://www.cs.wisc.edu/condor
69
Statistical Bootstrap
› Build up from the worker side out
› The matlab/octave worker:
› worker.m:
#!/s/octave/bin/octave -q
load "subset" subset;
subset = subset(floor(rand(10,1) .*
1000));
printf("%f ", mean(subset));
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70
Run the worker alone
› (won’t work – why?)
› ./worker.m
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Submit file
universe = vanilla
executable = worker.m
should_transfer_files = true
when_to_transfer_output = on_exit
transfer_input_files = subset
output = mean.$(PROCESS)
error
= foo
log = log
queue 10
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72
Create the initial data
driver.m
#!/s/octave/bin/octave –q
dist_size = 100000;
d = rand(dist_size, 1) .* 500;
subset = d(floor(rand(1000,1) .*
100000));
save "subset" subset;
http://www.cs.wisc.edu/condor
73
And submit the job…
› condor_submit submit
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74
Add the submission to
the driver script…
#!/s/octave/bin/octave –q
dist_size = 100000;
d = rand(dist_size, 1) .* 500;
subset = d(floor(rand(1000,1) .* 100000));
save "subset" subset;
system("condor_submit submit");
system("condor_wait log");
http://www.cs.wisc.edu/condor
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And run the driver!
› ./driver.m
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Parallel convergence
checking:
Another DAGman example
› Evaluating a function at many points
› Check for convergence -> retry
› Particle Swarm Optimization
http://www.cs.wisc.edu/condor
77
Prepare
Compute
Compute
Compute
Converge?
Compute
No
Yes!
Done
http://www.cs.wisc.edu/condor
78
Any Guesses?
› Who has thoughts?
› Best to work from “inside out”
http://www.cs.wisc.edu/condor
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The job itself.
#!/bin/sh
###### random.sh
echo $RANDOM
exit 0
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The submit file
› Any guesses?
http://www.cs.wisc.edu/condor
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The submit file
# submitRandom
universe = vanilla
executable = random.sh
Should_transfer_files = yes
When_to_transfer_output = on_exit
output = out
log = log
queue
http://www.cs.wisc.edu/condor
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Next step: the inner DAG
Node0
Node1
First
Node2
Node3
Node4
Last
Node
Node11
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The DAG file
› Any guesses?
http://www.cs.wisc.edu/condor
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The inner DAG file
Job Node0 submitRandom
Job Node1 submitRandom
Job Node2 submitRandom
Job Node3 submitRandom
PARENT Node0 CHILD Node1
PARENT Node0 CHILD Node2
PARENT Node0 CHILD Node3
Job Node11 submitRandom
PARENT Node1, Node2, Node3 CHILD Node11
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Inner DAG
› Does this work?
› At least one iteration?
http://www.cs.wisc.edu/condor
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How to iterate
› DAGman has simple control structures
(Makes it reliable)
› SUBDAGs!
› Remember what happens if post fails?
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The Outer Dag
› Another Degenerate Dag
(But Useful!)
t
SubDag (with retry)
Post Script (with exit value)
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This one is easy!
› Can you do it yourself?
http://www.cs.wisc.edu/condor
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The outer DAG file
####### Outer.dag #############
SUBDAG EXTERNAL A inner.dag
SCRIPT POST A converge.sh
RETRY A 10
#### converge.sh could look like
#!/bin/sh
echo "Checking convergence" >> converge
exit 1
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Let’s run that…
› condor_submit_dag outer.dag
› Does it work? How can you tell?
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DAGman a bit verbose…
$ condor_submit_dag outer.dag
----------------------------------------------------------------------File for submitting this DAG to Condor
: submit.dag.condor.sub
Log of DAGMan debugging messages
: submit.dag.dagman.out
Log of Condor library output
: submit.dag.lib.out
Log of Condor library error messages
: submit.dag.lib.err
Log of the life of condor_dagman itself
: submit.dag.dagman.log
-no_submit given, not submitting DAG to Condor.
You can do this with:
"condor_submit submit.dag.condor.sub"
--------------------------------------------------------------------------------------------------------------------------------------------File for submitting this DAG to Condor
: outer.dag.condor.sub
Log of DAGMan debugging messages
: outer.dag.dagman.out
Log of Condor library output
: outer.dag.lib.out
Log of Condor library error messages
: outer.dag.lib.err
http://www.cs.wisc.edu/condor
Log of the life of condor_dagman itself
: outer.dag.dagman.log
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Debugging helps
› Look in the user log file, “log”
› Look in the DAGman debugging log
› “foo”.dagman.out
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What does converge.sh
need
› Note the output files?
› How to make them unique?
› Add DAG variables to inner dag
And submitRandom file
http://www.cs.wisc.edu/condor
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The submit file (again)
# submitRandom
universe = vanilla
executable = random.sh
output = out
log = log
queue
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The submit file
# submitRandom
universe = vanilla
executable = random.sh
output = out.$(NodeNumber)
log = log
queue
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The inner DAG file (again)
Job Node0 submit_pre
Job Node1 submitRandom
Job Node2 submitRandom
Job Node3 submitRandom
PARENT Node0 CHILD Node1
PARENT Node0 CHILD Node2
PARENT Node0 CHILD Node3
Job Node11 submit_post
PARENT Node1 CHILD Node11
PARENT Node2 CHILD Node11
PARENT Node3 CHILD Node11
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The inner DAG file (again)
Job Node0 submit_pre
Job Node1 submitRandom
Job Node2 submitRandom
Job Node3 submitRandom
…
VARS Node1 NodeNumber=“1”
VARS Node2 NodeNumber=“2”
VARS Node3 NodeNumber=“3”
…
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Then converge.sh sees:
$ ls out.*
out.1 out.10 out.2 out.3 out.4
out.6 out.7 out.8 out.9
out.5
$
› And can act accordingly…
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Thank you!
Check us out on the Web:
http://www.condorproject.org
Email:
condor-admin@cs.wisc.edu
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