Massively parallel on single core? Post: 302395115

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Special Forums UNIX and Linux Applications High Performance Computing Massively parallel on single core? Post 302395115 by Andre_Merzky on Monday 15th of February 2010 04:23:34 AM

02-15-2010

Registered User

Hi Neo,

thanks for your reply!

I agree abut your remark as distributed architectures. This is my day-job, and I like it a lot :-)

I did not make the problem clear enough I think: the workload I am talking about are mostly idle jobs, so the CPU and memory load for each job is *very* low. Yes, I can beat the problem with more cores or nodes, but that seems very much like a waste, as those would be all idling most of the time.

Assume you plan for 1000 threads per core, and use quad code nodes - that would require 25 nodes which all idle all day long :-(

Some more detail, if that helps: the idle processes/threads are basically watchers, which represent a CPU/Memory heavy remote job they spawned, and whose state they are watching. Only when that state changes they become active, and kick of data movements or spawn new jobs.

We can't control the design of the remote job startup API very well (third party, synchronous API only), thus our technical options for obtaining state information about those jobs are limited, and boil down to

Code:

void * run_job (void * data)
{
   // this call runs a remote job, and blocks for hours
   remote_api_call (data);
   store_output_data (data);
}

#define NJOBS 100000

int main ()
{
  pthread_t threads[NJOBS]
  for ( int i = 0; i < NJOBS; i++ )
  {
     pthread_create (threads[i],  run_job, ...)
  }

  for ( int i = 0; i < NJOBS; i++ )
  {
     pthread_join (threads[i]);
  }
}

So, I can throw 25 nodes on that large for loop, and that is what we do basically - but what a waste...

The *real* workload are 100.000 CPU/Memory heavy remote jobs, which have sufficient resources to run concurrently. I am talking about the management side (our workflow engine).

Thanks, Andre.

Andre_Merzky

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