1. Parallel Computing in Matlab An Introduction

2. Overview Offload work from client to workers Run as many as eight workers (newest version) Can keep client session free for interactive work

3. Parallel for-loops (parfor) No iterations may depend on other iterations No global variables may be changed in the parfor loop There is some overhead

4. Using parfor Use “matlabpool open local 2” to open two workers (duo core) Use parfor like a for loop When finished, use matlabpool close See example: Parforloop.m See example: test.m

5. Batch Job Offload work to another session Continue using the client interactively Requires a few more commands than parfor

6. Batch Job job=batch('script_name') wait(job) load(job,'variable_name') destroy(job) See example three

7. Batch Parallel Loop Offload work Run in parallel

8. Batch Parallel Loop job=batch('script_name','matlabpool',1) Here we have one worker in addition to the one running the batch script for a total of two wait(job) load(job,'variable_name') destroy(job)