Re: [Gems-users] Discrepancy in Ruby Statistics

[Dan Gibson <degibson@xxxxxxxx>]

There could be several things going on:

1) To verify the setup: Are you issuing identical commands to _Simics_? e.g. dstc-disable, cpu-switch-time 1, etc.?

2) The RANDOM_SEED will vary from run to run unless you change it. If your workload is sensitive to lock acquisition order (most are) then it can make a big difference. This is why we run each data point many times to achieve 95% confidence intervals. Since the Ruby_cycles difference is only about 2%, it could be easily attributable to differences in RANDOM_SEED.

3) Resolving locks in a particular order *is* random noise, but it is not something that should be discarded from simulations -- real applications will acquire locks in many different orders, just as the simulator does. A sound methodology would be to run the same simulation a few more times and take an average, rather than to "decide between A and B".

Regards,
Dan

Nitin Bhardwaj wrote:

Hi,

My doubt is in statistics produced by Ruby+Simics simulation's.

If I have 2 copies of simulator in different login's (A and B with same versions of GEMS and SIMICS) and if I run the same binary on both the simulator's, load same slicc protocol, use same ruby configuration then will the results produced from two simulations be similar or not? If they are not exactly similar then can there be a significant difference in the results. Below are some statistics I am gathering from the two simulations ran for 16 Processor configuration. Both the runs use same starting checkpoint, runs the same application binary, thread binding is applied in application, randomization is off, at the first magic breakpoint ruby statistics gets cleared.

Protocol	Ruby_cycles	L1DMiss	L1IMiss	L2Miss	Simics_cycles	Instruction	L1Load	L1Ifetch	L1Store
Sim A	48027564	57392	9845	12811	96055128	46668403	8947306	9845	3380127
Sim B	49265138	79726	6525	21283	98530276	42282268	8690709	6525	4649997

What could be the reason for such a huge difference in results e.g. ruby cycles differ by 1237574. Now, because of this discrepancy in results the performance benefit (in terms of ruby cycles) while comparing two slicc protocols varies in two simulation models. The other observation is that both the simulation models A and B always produces same results on multiple runs (for the same application).

My question is basically,
1.) Is this variation justified in results or do you think there is something wrong in the set-up?
2.) If this variation is justified to some extent and hoping there is nothing wrong in the set-up then what could be reason for this variation?
3.) How can I choose a model (A or B) to measure the performance benefit (with confidence) that this performance is not because of some random noise due to OS or resolving locks in different order or something else unknown?

I would really appreciate any help in resolving this issue.

-Thank You
Nitin Bhardwaj





 

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