Can profiling be used to verify if optimization was successful?


I know that profiling is useful to identify bottlenecks and
determining what parts of the code require how much time to execute.
The latter isn't always very easy to track in the midst of other paths
being executed, so once I decide what I want to optimize it might be
problematic to see the improvement in numbers. This is especially true
in desktop apps which run constantly and it is difficult to: execute
the same path and execute it the same number of times to have reliable
comparison.



It won't help me if before optimization the function ran X times
and took 500 milliseconds, and after optimization it run Y times and
took 400 milliseconds.



In such cases, can I somehow use a profiler to determine
improvement or do I have to resolve to other options?

There has been a problem with K3b doing a verify and the verify fails.
When you manually check the validity of the burn, it is ok. So burn
ok, verify fails.
This problem appeared in 8.04. 7.10 works as
expected.
Problem seen with burning iso's. Assume same will
happen with regular projects.
Reading on the internet, this
problem has been linked to the kernal, not k3b.
Is there a
work-around or has this been fixed. Please provide details on on
either
item ( work-around or fix ).
I am running 8.04.2
ubuntu load with kubuntu desktop loaded on top
Here is uname -a
to provide kernal/platform details
Linux ubuntu 2.6
Ubuntu
Hi Guys,
I've got a potential new client with existing linux
systems, normally that doesn't bother me but I already know that at
least one of the systems "is a bit quirky" and will only run
it's bespoke app with specific versions of software running on the
box.
I was wondering what every one does when it comes to
profiling a server? Before I look to see if I can migrate their app
to a new server / platform I want to make sure I know everything there
is to know about the current installed server.
Ubuntu
Anybody have any experience profiling applications that use SWIG? />I am looking to profile code that is written in c++ with a
Python/SWIG wrapper. If I use gprof, is it enough to just compile the
c++ code with -pg or will I have to recompile
Python/SWIG/NumPy/etc?
If I use something like oprofile will SWIG
obfuscate the profiling process?
Ubuntu

A logwatch report outputted the following message.



A total of 1 possible successful probes were detected (the
following URLs
contain strings that match one or more of a listing of strings that
indicate a possible exploit):

/?_SERVER[DOCUMENT_ROOT]=../../../../../../../../../../../etc/passwd%00
HTTP Response 200


I am aware that this match is based on a predefined list of strings
from Logwatch and that it is a possible exploit but I
am unsure how to investigate further to be certain it is not one.




  1. Is it enough to just visit this url in the browser and check if
    there is no private information being outputted or are there other
    methods/places I need to check?


  2. Does the HTTP response 200 means it reached the /etc/passwd
    directory?


Network & Servers

I have noticed this wierd behaviour during CUDA code profiling
using nvprof or nvvp. Instead of the actual values of the counters, it
displays an overflow.



For example, I profile my application using



 nvprof --print-gpu-trace --metrics 
warp_execution_efficiency ./CUDA-EC


And the result I am getting is this:



Device           Kernel                      Warp Execution
Efficiency
Tesla K20m (0) fix_errors1_warp_cop <OVERFLOW>


Can somebody tell me how to avoid this and fetch actual value? This
behaviour also occurs when I use nvvp.

Web Development

I know that profiling is useful to identify bottlenecks and
determining what parts of the code require how much time to execute.
The latter isn't always very easy to track in the midst of other paths
being executed, so once I decide what I want to optimize it might be
problematic to see the improvement in numbers. This is especially true
in desktop apps which run constantly and it is difficult to: execute
the same path and execute it the same number of times to have reliable
comparison.



It won't help me if before optimization the function ran X times
and took 500 milliseconds, and after optimization it run Y times and
took 400 milliseconds.



In such cases, can I somehow use a profiler to determine
improvement or do I have to resolve to other options?

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