On Thursday, May 8, 2003, at 11:07 America/Denver, Beman Dawes wrote:
At 11:11 AM 5/8/2003, Darin Adler wrote:
>On Thursday, May 8, 2003, at 07:04 AM, Beman Dawes wrote:
>
>> A 2-3% timing difference probably isn't reliably repeatable in real
>> code.
>>
>> How code and data happens to land in hardware caches can easily
swamp
>> out such a small difference. The version-to-version or step-to-step
>> differences in CPU's, memory, compilers, or operating systems can
>> cause that much difference in a given program. Differences need to
get
>> up into the 20-30% range before they are likely to be reliably
>> repeatable across different systems.
>>
>> At least that's been my experience.
>
>That has not been my recent experience. While working on my current
>project (the Safari web browser), we have routinely made 1% speedups
>that are measurable and have an effect across multiple machines and
>compilers (same basic CPU type and operating system), and we have also
>detected 1% slowdowns when we inadvertently introduced them.
I notice the examples you give are JavaScript. Greg's example of a
virtual machine is written mostly in C, IIRC. I wonder if C++ is more
sensitive to compiler differences?
For example, some C++ compilers are a lot more aggressive about
inlining than others. For some of the code I've timed, a change slowed
results for a compiler that failed to inline it, but ran quicker for
the compiler that was good at inlining.
Makes sense. Boost code stresses compilers in ways that our code
doesn't -- the need to be as portable as we are means we don't
even use all the features of C89, let alone C++ or C99. And of
course C89 doesn't have things like inlining and virtual function
dispatch that can vary so much across C++ compilers. Plus we
spend a fair amount of time inspecting the output of our compilers
and tweaking our C code until we get what we want, and preserving
the tweaks in platform-specific macros.
The fact remains that it takes a lot of 3% tweaks to make a big
difference, so until you know you have the best possible data
structures and algorithms there isn't much point, and when there
is a point it is painstaking work at the limits of measurability.
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