mirror of https://github.com/BOINC/boinc.git
81 lines
2.8 KiB
PHP
81 lines
2.8 KiB
PHP
<?php
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require_once("docutil.php");
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page_head("More about benchmarks");
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echo "
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<h2>How benchmarks are calculated</h2>
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<p>
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'Whetstone' is the name of the benchmark that is reported on your
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[Show computers] web page as 'Measured floating point speed'.
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Dhrystone is the name of the benchmark used for 'Measured integer speed'.
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Floats can have fractional parts (like 1.48283 or 3.141592);
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integers are whole numbers like 1, 2, 938283 or 2004.
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Whetstone does 8 different groups of tests (repeatedly of course),
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times how long they took to finish, and produces a number,
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[ops performed]/[time].
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These tests all use floating point math operations of the CPUs being tested.
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Some of them are simple math (addition, multiplication, division)
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while others compute trigonometric and exponential functions
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(sine, cosine, tangent, exponent).
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Dhrystone checks repeated integer operations
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and several operating system file handling operations.
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<p>
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Neither of the tests really checks how well/fast a system can access memory,
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and SETI@home (for example) accesses memory a lot.
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<p>
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Here is an example of memory introducing a delay:
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A Pentium 4 CPU of any speed can calculate the sine of an angle in
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approximately 170 ticks of its internal clock.
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It could have performed 170 regular integer additions in this time.
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<p>
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But if it wanted to do an integer addition on a number somewhere out in memory
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(say it was working on a table of numbers), the
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CPU might have to wait as much as 260 ticks
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for this memory integer to be delivered to the CPU.
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So a badly timed integer+memory
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operation would take far longer than a sine calculation.
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<p>
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This is where Celeron CPUs can really slow down.
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Pentium has many features to predict when the CPU might be getting memory,
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and begins getting it long before the CPU actually calculates with it.
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Thus there is much less delay for most memory operations.
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<h2>Why 'predicted time' can be wrong</h2>
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Each WU delivered to your machine includes an estimated number of
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floating point (FP) calculations.
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BOINC divides this by the FP
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benchmark number to estimate completion time.
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SETI@home's WUs estimate number is currently always 27.9 trillion (american),
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however the actual number of FP ops varies greatly which is why
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WUs take different amounts of time to finish.
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<p>
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SETI@home uses almost all single-precision floating point math,
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while Whetstone is all double-precision math.
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On Intel x86 processors
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the speed difference in calculating single vs. double isn't very large.
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<p>
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SETI@home uses mostly add, sub, multiply and divide.
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About 20% of its time is spent in trigonometry.
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Almost all the time in Whetstone is used for trigonometry.
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<p>
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Memory access speed and trigonometry are the two major reasons that
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the benchmark results and SETI@home processing speed don't match
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up on many systems.
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<br><br>
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<i>Thanks to Ben Herndon for this writeup</i>
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";
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page_tail();
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?>
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