run batch parallel jobs -凯发k8网页登录

run batch parallel jobs

run a batch job

to offload work from your matlab^® session to run in the background in another session, you can use the command inside a script.

to create the script, type:
```
edit mywave
```

in the matlab editor, create a for-loop:

for i = 1:1024
  a(i) = sin(i*2*pi/1024);
end

save the file and close the editor.
use the batch command in the matlab command window to run your script on a separate matlab worker:
```
job = batch('mywave')
```
batch does not block matlab and you can continue working while computations take place. if you need to block matlab until the job finishes, use the wait function on the job object.
```
wait(job)
```
after the job finishes, you can retrieve and view its results. the load command transfers variables created on the worker to the client workspace, where you can view the results:
```
load(job,'a')
plot(a)
```
when the job is complete, permanently delete its data and remove its reference from the workspace:
```
delete(job)
clear job
```

batch runs your code on a local worker or a cluster worker, but does not require a parallel pool.

you can use batch to run either scripts or functions. for more details, see the reference page.

run a batch job with a parallel pool

you can combine the abilities to offload a job and run a loop in a parallel pool. this example combines the two to create a simple batch parfor-loop.

to create a script, type:
```
edit mywave
```

in the matlab editor, create a parfor-loop:

parfor i = 1:1024
  a(i) = sin(i*2*pi/1024);
end

save the file and close the editor.
run the script in matlab with the batch command. indicate that the script should use a parallel pool for the loop:
```
job = batch('mywave','pool',3)
```
this command specifies that three workers (in addition to the one running the batch script) are to evaluate the loop iterations. therefore, this example uses a total of four local workers, including the one worker running the batch script. altogether, there are five matlab sessions involved, as shown in the following diagram.
to view the results:
```
wait(job)
load(job,'a')
plot(a)
```
the results look the same as before, however, there are two important differences in execution:
- the work of defining the parfor-loop and accumulating its results are offloaded to another matlab session by batch.
- the loop iterations are distributed from one matlab worker to another set of workers running simultaneously ('pool' and parfor), so the loop might run faster than having only one worker execute it.
when the job is complete, permanently delete its data and remove its reference from the workspace:
```
delete(job)
clear job
```

run script as batch job from the current folder browser

from the current folder browser, you can run a matlab script as a batch job by browsing to the file’s folder, right-clicking the file, and selecting run script as batch job. the batch job runs on the cluster identified by the default cluster profile. the following figure shows the menu option to run the script file script1.m:

running a script as a batch from the browser uses only one worker from the cluster. so even if the script contains a parfor loop or spmd block, it does not open an additional pool of workers on the cluster. these code blocks execute on the single worker used for the batch job. if your batch script requires opening an additional pool of workers, you can run it from the command line, as described in run a batch job with a parallel pool.

when you run a batch job from the browser, this also opens the job monitor. the job monitor is a tool that lets you track your job in the scheduler queue. for more information about the job monitor and its capabilities, see .

run batch parallel jobs -凯发k8网页登录