The Intel Compiler 14.0.0 claims version GCC 4.7.3 compatibility
via __GNUC__/__GNUC__MINOR__ macros, but does not provide the same
level of GCC vector extensions support as the original GCC compiler:
http://gcc.gnu.org/onlinedocs/gcc/Vector-Extensions.html
Which results in the following compilation failure:
In file included from ../test/utils.h(7),
from ../test/utils.c(3):
../test/utils-prng.h(138): error: expression must have integral type
uint32x4 e = x->a - ((x->b << 27) + (x->b >> (32 - 27)));
^
The problem is fixed by doing a special check in configure for
this feature.
Current blitters-test program had difficulties detecting a bug in
over_n_8888_8888_ca implementation for MIPS DSPr2:
http://lists.freedesktop.org/archives/pixman/2013-March/002645.html
In order to hit the buggy code path, two consecutive mask values had
to be equal to 0xFFFFFFFF because of loop unrolling. The current
blitters-test generates random images in such a way that each byte
has 25% probability for having 0xFF value. Hence each 32-bit mask
value has ~0.4% probability for 0xFFFFFFFF. Because we are testing
many compositing operations with many pixels, encountering at least
one 0xFFFFFFFF mask value reasonably fast is not a problem. If a
bug related to 0xFFFFFFFF mask value is artificialy introduced into
over_n_8888_8888_ca generic C function, it gets detected on 675591
iteration in blitters-test (out of 2000000).
However two consecutive 0xFFFFFFFF mask values are much less likely
to be generated, so the bug was missed by blitters-test.
This patch addresses the problem by also randomly setting the 32-bit
values in images to either 0xFFFFFFFF or 0x00000000 (also with 25%
probability). It allows to have larger clusters of consecutive 0x00
or 0xFF bytes in images which may have special shortcuts for handling
them in unrolled or SIMD optimized code.
This adds a fast SIMD-optimized variant of a small noncryptographic
PRNG originally developed by Bob Jenkins:
http://www.burtleburtle.net/bob/rand/smallprng.html
The generated pseudorandom data is good enough to pass "Big Crush"
tests from TestU01 (http://en.wikipedia.org/wiki/TestU01).
SIMD code uses http://gcc.gnu.org/onlinedocs/gcc/Vector-Extensions.html
which is a GCC specific extension. There is also a slower alternative
code path, which should work with any C compiler.
The performance of filling buffer with random data:
Intel Core i7 @2.8GHz (SSE2) : ~5.9 GB/s
ARM Cortex-A15 @1.7GHz (NEON) : ~2.2 GB/s
IBM Cell PPU @3.2GHz (Altivec) : ~1.7 GB/s
