** Description changed:
+ SRU Justification
+ =================
+
+ [Impact]
+
+ * Severe performance hit on many maths-heavy workloads. For example, a
+ user reports linpack performance of 13 Gflops on Trusty and Bionic and
+ 3.9 Gflops on Xenial.
+
+ * Because the impact is so large (>3x) and Xenial is supported until
+ 2021, the fix should be backported.
+
+ * The fix avoids an AVX-SSE transition penalty. It stops
+ _dl_runtime_resolve() from using AVX-256 instructions which touch the
+ upper halves of various registers. This change means that the processor
+ does not need to save and restore them.
+
+ [Test Case]
+
+ Firstly, you need a suitable Intel machine. Users report that Sandy
+ Bridge, Ivy Bridge, Haswell, and Broadwell CPUs are affected, and I
+ have been able to reproduce it on a Skylake CPU using a suitable Azure
+ VM.
+
+ Create the following C file, exp.c:
+
+ #include <math.h>
+ #include <stdio.h>
+
+ int main () {
+ double a, b;
+ for (a = b = 0.0; b < 2.0; b += 0.00000005) a += exp(b);
+ printf("%f\n", a);
+ return 0;
+ }
+
+ $ gcc -O3 -march=x86-64 -o exp exp.c -lm
+
+ With the current version of glibc:
+
+ $ time ./exp
+ ...
+ real 0m1.349s
+ user 0m1.349s
+
+
+ $ time LD_BIND_NOW=1 ./exp
+ ...
+ real 0m0.625s
+ user 0m0.621s
+
+ Observe that LD_BIND_NOW makes a big difference as it avoids the call to
+ _dl_runtime_resolve.
+
+ With the proposed update:
+
+ $ time ./exp
+ ...
+ real 0m0.625s
+ user 0m0.621s
+
+
+ $ time LD_BIND_NOW=1 ./exp
+ ...
+
+ real 0m0.631s
+ user 0m0.631s
+
+ Observe that the normal case is faster, and LD_BIND_NOW makes a
+ negligible difference.
+
+ [Regression Potential]
+
+ glibc is the nightmare case for regressions as could affect pretty much
+ anything, and this patch touches a key part (dynamic libraries).
+
+ We can be fairly confident in the fix generally - it's in the glibc in
+ Bionic, Debian and some RPM-based distros. The backport is based on
+ the patches in the release/2.23/master branch in the upstream glibc
+ repository, and the backport was straightforward.
+
+ Obviously that doesn't remove all risk. There is also a fair bit of
+ Ubuntu-specific patching in glibc so other distros are of limited
+ value for ruling out bugs. So I have done the following testing, and
+ I'm happy to do more as required. All testing has been done:
+ - on an Azure VM (affected by the change), with proposed package
+ - on a local VM (not affected by the change), with proposed package
+
+ * Boot with the upgraded libc6.
+
+ * Watch a youtube video in Firefox over VNC.
+
+ * Build some C code (debuild of zlib).
+
+ * Test Java by installing and running Eclipse.
+
+ Autopkgtest also passes.
+
+ [Original Description]
+
Bug [0] has been introduced in Glibc 2.23 [1] and fixed in Glibc 2.25
[2]. All Ubuntu versions starting from 16.04 are affected because they
use either Glibc 2.23 or 2.24. Bug introduces serious (2x-4x)
performance degradation of math functions (pow, exp/exp2/exp10,
log/log2/log10, sin/cos/sincos/tan, asin/acos/atan/atan2,
sinh/cosh/tanh, asinh/acosh/atanh) provided by libm. Bug can be
reproduced on any AVX-capable x86-64 machine.
@strikov: According to a quite reliable source [5] all AMD CPUs and
latest Intel CPUs (Skylake and Knights Landing) don't suffer from
AVX/SSE transition penalty. It means that the scope of this bug becomes
smaller and includes only the following generations of Intel's CPUs:
Sandy Bridge, Ivy Bridge, Haswell, and Broadwell. Scope still remains
quite large though.
@strikov: Ubuntu 16.10/17.04 which use Glibc 2.24 may recieve the fix
from upstream 2.24 branch (as Marcel pointed out, fix has been
backported to 2.24 branch where Fedora took it successfully) if such
synchronization will take place. Ubuntu 16.04 (the main target of this
bug) uses Glibc 2.23 which hasn't been patched upstream and will suffer
from performance degradation until we fix it manually.
This bug is all about AVX-SSE transition penalty [3]. 256-bit YMM
registers used by AVX-256 instructions extend 128-bit registers used by
SSE (XMM0 is a low half of YMM0 and so on). Every time CPU executes SSE
instruction after AVX-256 instruction it has to store upper half of the
YMM register to the internal buffer and then restore it when execution
returns back to AVX instructions. Store/restore is required because old-
fashioned SSE knows nothing about the upper halves of its registers and
may damage them. This store/restore operation is time consuming (several
tens of clock cycles for each operation). To deal with this issue, Intel
introduced AVX-128 instructions which operate on the same 128-bit XMM
register as SSE but take into account upper halves of YMM registers.
Hence, no store/restore required. Practically speaking, AVX-128
instructions is a new smart form of SSE instructions which can be used
together with full-size AVX-256 instructions without any penalty. Intel
recommends to use AVX-128 instructions instead of SSE instructions
wherever possible. To sum things up, it's okay to mix SSE with AVX-128
and AVX-128 with AVX-256. Mixing AVX-128 with AVX-256 is allowed because
both types of instructions are aware of 256-bit YMM registers. Mixing
SSE with AVX-128 is okay because CPU can guarantee that the upper halves
of YMM registers don't contain any meaningful data (how one can put it
there without using AVX-256 instructions) and avoid doing store/restore
operation (why to care about random trash in the upper halves of the YMM
registers). It's not okay to mix SSE with AVX-256 due to the transition
penalty. Scalar floating-point instructions used by routines mentioned
above are implemented as a subset of SSE and AVX-128 instructions. They
operate on a small fraction of 128-bit register but still considered
SSE/AVX-128 instruction. And they suffer from SSE/AVX transition penalty
as well.
Glibc inadvertently triggers a chain of AVX/SSE transition penalties due
to inappropriate use of AVX-256 instructions inside
_dl_runtime_resolve() procedure. By using AVX-256 instructions to
push/pop YMM registers [4], Glibc makes CPU think that the upper halves
of XMM registers contain meaningful data which needs to be preserved
during execution of SSE instructions. With such a 'dirty' flag set every
switch between SSE and AVX instructions (AVX-128 or AVX-256) leads to a
time consuming store/restore procedure. This 'dirty' flag never gets
cleared during the whole program execution which leads to a serious
overall slowdown. Fixed implementation [2] of _dl_runtime_resolve()
procedure tries to avoid using AVX-256 instructions if possible.
Buggy _dl_runtime_resolve() gets called every time when dynamic linker
tries to resolve a symbol (any symbol, not just ones mentioned above).
It's enough for _dl_runtime_resolve() to be called just once to touch
the upper halves of the YMM registers and provoke AVX/SSE transition
penalty in the future. It's safe to say that all dynamically linked
application call _dl_runtime_resolve() at least once which means that
all of them may experience slowdown. Performance degradation takes place
when such application mixes AVX and SSE instructions (switches from AVX
to SSE or back).
There are two types of math routines provided by libm:
(a) ones that have AVX-optimized version (exp, sin/cos, tan, atan, log and
other)
(b) ones that don't have AVX-optimized version and rely on general purpose
SSE implementation (pow, exp2/exp10, asin/acos, sinh/cosh/tanh,
asinh/acosh/atanh and others)
For the former group of routines slowdown happens when they get called
from SSE code (i.e. from the application compiled with -mno-avx) because
SSE -> AVX transition takes place. For the latter one slowdown happens
when routines get called from AVX code (i.e. from the application
compiled with -mavx) because AVX -> SSE transition takes place. Both
situations look realistic. SSE code gets generated by gcc to target
x86-64 and AVX-optimized code gets generated by gcc -march=native on
AVX-capable machines.
============================================================================
Let's take one routine from the group (a) and try to reproduce the
slowdown.
#include <math.h>
#include <stdio.h>
int main () {
double a, b;
for (a = b = 0.0; b < 2.0; b += 0.00000005) a += exp(b);
printf("%f\n", a);
return 0;
}
$ gcc -O3 -march=x86-64 -o exp exp.c -lm
$ time ./exp
<..> 2.801s <..>
$ time LD_BIND_NOW=1 ./exp
<..> 0.660s <..>
You can see that application demonstrates 4x better performance when
_dl_runtime_resolve() doesn't get called. That's how serious the impact
of AVX/SSE transition can be.
============================================================================
Let's take one routine from the group (b) and try to reproduce the
slowdown.
#include <math.h>
#include <stdio.h>
int main () {
double a, b;
for (a = b = 0.0; b < 2.0; b += 0.00000005) a += pow(M_PI, b);
printf("%f\n", a);
return 0;
}
# note that -mavx option has been passed
$ gcc -O3 -march=x86-64 -mavx -o pow pow.c -lm
$ time ./pow
<..> 4.157s <..>
$ time LD_BIND_NOW=1 ./pow
<..> 2.123s <..>
You can see that application demonstrates 2x better performance when
_dl_runtime_resolve() doesn't get called.
============================================================================
[!] It's important to mention that the context of this bug might be even
wider. After a call to buggy _dl_runtime_resolve() any transition
between AVX-128 and SSE (otherwise legitimate) will suffer from
performance degradation. Any application which mixes AVX-128 floating
point code with SSE floating point code (e.g. by using external SSE-only
library) will experience serious slowdown.
[0] https://sourceware.org/bugzilla/show_bug.cgi?id=20495
[1]
https://sourceware.org/git/?p=glibc.git;a=commit;h=f3dcae82d54e5097e18e1d6ef4ff55c2ea4e621e
[2]
https://sourceware.org/git/?p=glibc.git;a=commit;h=fb0f7a6755c1bfaec38f490fbfcaa39a66ee3604
[3]
https://software.intel.com/en-us/articles/intel-avx-state-transitions-migrating-sse-code-to-avx
[4]
https://sourceware.org/git/?p=glibc.git;a=blob;f=sysdeps/x86_64/dl-trampoline.h;h=d6c7f989b5e74442cacd75963efdc6785ac6549d;hb=fb0f7a6755c1bfaec38f490fbfcaa39a66ee3604#l182
[5] http://www.agner.org/optimize/blog/read.php?i=761#761
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https://bugs.launchpad.net/bugs/1663280
Title:
Serious performance degradation of math functions
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