x86 linux boot is a component of the '--length long' regression.
You need the kernel and disk image that are installed when the regression
is run.

command line:
 ./build/X86/gem5.opt ./tests/gem5/x86-boot-tests/run_exit.py --kernel
boot-test/vmlinux-4.19.83 --disk boot-test/base.img --cpu-type atomic
--num-cpus 1 --boot-type init



On Sat, Oct 10, 2020 at 10:22 PM Gabe Black via gem5-dev <[email protected]>
wrote:

> I'm planning to give this a shot, but is there a simple command line for
> this? It would take a lot of time to set up a system and all that, and it
> would be much nicer to just fire off, for instance, a linux boot test if we
> already have something lying around.
>
> Gabe
>
> On Wed, Oct 7, 2020 at 10:41 AM Jason Lowe-Power <[email protected]>
> wrote:
>
>> I think Linux boot is pretty reasonable. Or, Linux boot + some
>> multithreaded tests (parsec is available for x86 in gem5-resources). If
>> there isn't much performance impact there, I think that would be strong
>> evidence for little performance impact, generally.
>>
>> Cheers,
>> Jason
>>
>> On Mon, Oct 5, 2020 at 3:07 AM Gabe Black via gem5-dev <[email protected]>
>> wrote:
>>
>>> Hey folks. I'm trying out using dynamically allocated arrays to track
>>> source and destination register indices in static and dynamic instructions
>>> rather than fixed size arrays and would like to check what the impact on
>>> performance is. I used to use the twolf SPEC benchmark for that since it
>>> was fairly quick and easy to run but still ran long enough to get
>>> meaningful results, but do we have something like that now that's maybe
>>> even easier to set up? Or is easier for other people to run?
>>>
>>> As far as the arrays, what I'm aiming at is to make it unnecessary to
>>> measure the max number of indices needed and hence the minimum size of
>>> those arrays since that centralized global value needs to reflect every
>>> instruction in gem5, and it would be a bit of a pain to coordinate that
>>> with multiple ISAs. Allocating those arrays statically as part of the
>>> StaticInst or DynInst classes makes allocation cheaper since it just makes
>>> the classes a little bigger, and making them dynamic will inevitably
>>> involve secondary allocations to give the vectors (for instance) their
>>> backing store. I'm hopeful it won't be that bad though, since StaticInsts
>>> are usually reused from a cache and not reallocated, and dynamic
>>> instructions are used in CPUs which already have lots of other, more
>>> substantial overhead.
>>>
>>> Gabe
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