Hi Paul,

I am sorry but I don't quite get it. How do I assure the applications are
using the extra cores?

FYI, here is what I used in the command line to run blackscholes with 4
cores:

%./build/ALPHA_FS/gem5.opt configs/example/ruby_fs.py
--script=./PARSEC/4-core/blackscholes/blackscholes_4c_simsmall.rcS
--cpu-type=timing --caches --l2cache --num-cpus=4 --num-dirs=4
--num-l2caches=4 --cpu-clock=1GHz --l1d_size=64kB --l1i_size=64kB
--l1d_assoc=2 --l1i_assoc=2 --l2_size=4MB --l2_assoc=8 --cacheline_size=64
--ruby --garnet-network=flexible --topology=Mesh --mesh-rows=2

Thanks,

Jia

On Mon, Aug 12, 2013 at 9:00 PM, Paul Rosenfeld <[email protected]>wrote:

> Are you certain that the applications are actually using the extra cores
> (i.e., are you setting flags for parsecmgmt like -n)? If a single thread
> runs on more simulated cores, I'd imagine that the runtime would be
> identical while the number of instructions would go up (due to idle threads
> running on the spare cores).
>
>
> On Mon, Aug 12, 2013 at 3:38 PM, Jia Zhan <[email protected]> wrote:
>
>> Hello,
>>
>> I am running a single benchmark with different number of cores to observe
>> the performance speedup. However I didn't see any reductions in *
>> sim_second*s when the number of cores increases from 1 to 16. Also, I
>> noticed that* sim_insts* (number of instructions simulated) also
>> increase as the number of cores increase. Isn't true that the number of
>> instructions should stay the same for a specific benchmark?
>>
>> Best,
>> Jia
>>
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>
>
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