Hi Subhasis Simulating both the client and the server is right way to do it. The super fast native client will change the server behavior and will give you inaccurate results. -Furat
On Tue, Oct 22, 2013 at 8:48 PM, Subhasis Das <[email protected]> wrote: > Hi Akanksha, > > Thanks a lot for the reply. We are simulating 500M instructions now. We > will try to simulate the server and client in different MARSS instances to > see whether that gives better results. > > FYI, if you are using the directions to run memcached from cloudsuite > page, the flags for running memcached are given wrong there. Specifically, > the command to run memcached should be ./memcached -m <amount of memory in > MB> ... instead of ./memcached -D <amount of memory in MB> .... The -D flag > actually turns on fine grained statistics collection in memcached which > consumes most of cycles in memcached. You can verify this by doing > ./memcached -h. When simulating with that configuration we also got miss > rates of ~ 10%, but it dropped when we used -m. > > -- > Subhasis > > > On Tue, Oct 22, 2013 at 8:25 PM, Akanksha Jain <[email protected]>wrote: > >> Subhasis, >> >> How many instructions are you simulating? It might be a good idea to >> run longer simulations to get representative miss rates because Cloud >> Suite benchmarks are fairly I/O intensive. On simulating a total of >> 250 million instructions with a single threaded server, my experiments >> show a miss rate of 11% for memcached. >> >> Also, are you running the client natively? Given that Marss is orders >> of magintude slower than native execution, you might try running the >> client in a separate instance of Marss to match the client's request >> rate to the server's processing rate. >> >> I did not attend the MICRO 2012 tutorial, so I am curious what changes >> were suggested to run Cloud Suite with Marss. In our experience so >> far, it takes an unrealistic amount of simulation time to warm up the >> caches. As a result, we observe very little memory activity when >> simulating 1-2 billion instructions (memcached was an exception). Our >> guess is that due to the JVM and I/O overheads, it takes Marss a >> really really long time to process enough data to warm up the caches. >> Also fast-forwarding through the initialization phase in a multi-core >> setting seems to hang a lot of times. Does anybody have any thoughts >> on these issues? >> >> On Tue, Oct 22, 2013 at 9:52 PM, Subhasis Das <[email protected]> >> wrote: >> > We are trying to study some datacenter applications and are trying to >> get >> > cloudsuite to work under Marssx86. >> > >> > We have some of the benchmarks from cloudsuite running under Marssx86. >> > However the simulated cache miss rate results seem to be very different >> from >> > cache miss rates obtained from native hardware using perf (e.g., for >> > memcached the native L1 miss rates are ~ 15%, whereas we observe only ~ >> 3%). >> > The setup we are using for simulation is to have the server workload >> running >> > in a single threaded simulated machine while we run the load generators >> from >> > outside and we use qemu's user mode networking. >> > >> > You mentioned in your MICRO 2012 tutorial that the work to simulate >> > cloudsuite under Marssx86 is ongoing. Is that work done? If yes, is it >> > possible for us to gain access to the necessary steps for simulating >> > cloudsuite on Marssx86, and/or the disk images used by you? >> > >> > -- >> > Thanks, >> > Subhasis >> > >> > _______________________________________________ >> > http://www.marss86.org >> > Marss86-Devel mailing list >> > [email protected] >> > https://www.cs.binghamton.edu/mailman/listinfo/marss86-devel >> > >> >> >> >> -- >> Thanks, >> Akanksha Jain >> PhD Candidate >> Department of Computer Science >> University of Texas at Austin >> > > > _______________________________________________ > http://www.marss86.org > Marss86-Devel mailing list > [email protected] > https://www.cs.binghamton.edu/mailman/listinfo/marss86-devel > >
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