Re: [Gems-users] Discrepancy in Ruby Statistics

[James Wang <jameswang99@xxxxxxxxx>]

Hi Nitin:
    There is an environment variable call RANDOM_SEED that you could set to a fixed number so that Ruby + Simics does not give you different results for different runs because OS might make different decisions using different RANDOM_SEED.
    The default setting of Ruby will have a different RANDOM_SEED every time you run it. You could change it in $GEMS/gen-scripts/microbench.py so that it use one fix number every time.

 

Regards
James

----- Original Message ----
From: Nitin Bhardwaj <bhardwaj@xxxxxxxxxxxxxxxx>
To: gems-users@xxxxxxxxxxx
Sent: Thursday, May 10, 2007 3:07:03 PM
Subject: [Gems-users] Discrepancy in Ruby Statistics

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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