[Swift-devel] Swift and BGP plots

[Mihael Hategan]

On Mon, 2009-10-26 at 16:36 -0500, Ioan Raicu wrote:
[...]

> For all the above stats, I don't understand why the minimum time is 
> 10~20 seconds, when the jobs are sleep 60? Or perhaps you were doing 
> sleep 0 here?

Well, I don't understand what the log plot tools mean by those numbers,
but it's clearly not the job time.

> > 64k jobs, 4000 workers:
> > http://www.mcs.anl.gov/~hategan/report-dc-4000/
> >   
> Shortest event (s): 106.119999885559
> Longest event (s): 1246.60699987411
> Mean event duration (s): 334.987874176266
> Standard deviation of event duration (s): 290.212811366649
> 
> Efficiency: 18%?

Well, I was a bit afraid that this will turn out into a numerology
exercise. I'm not sure whether to be happy or sad that I was right.

I'm not sure what "efficiency" is supposed to mean, but you can look at
a few things:
1. The coaster panel. That gives you average utilization of workers in
each block measured by the code that sends the requests to the workers.
It's obtained by dividing the time a CPU is known to be running a job
divided by the time a CPU is known to be running a job plus the time a
CPU is known to be sitting idle. I need to revise that a bit to account
for delays in sending the messages to the workers, but it should be
reasonably accurate. Those numbers are above 99% and therefore look
suspiciously high.
2. Multiply 60s with the number of jobs (65535), divide by the number of
workers (6*1024) and then by the total time since the first job starts
to when the last job finishes (or you could choose the middle of the
ramp-up to the middle of the ramp-down to get some sort of amortized
efficiency). That gives you about 91% end-to end and 96% amortized. Or
you could divide by the total time, including swift startup, partition
boot time, etc. to get 64%.

>From these you can derive various speedups, by multiplying those
percentages with the number of workers (6*1024).

[...]