Why is Intel Haswell XEON CPU sporadically miscomputing FFTs and ART?

Question

During the last days I observed a behaviour of my new workstation I couldn't explain. Doing some research on this problem, there might be a possible bug in the INTEL Haswell architecture as well as in the current Skylake Generation.

Before writing about the possible bug, let me give you an overview of the hardware used, the program code and the problem itself.

Workstation hardware specification

INTEL Xeon E5-2680 V3 2500MHz 30M Cache 12Core
Supermicro SC745 BTQ -R1K28B-SQ
4 x 32GB ECC Registered DDR4-2133 Ram
INTEL SSD 730 Series 480 GB
NVIDIA Tesla C2075
NVIDIA TITAN

Operating system & program code in question

I'm currently running Ubuntu 15.04 64bit Desktop version, latest updates and kernel stuff installed. Besides using this machine to develop CUDA Kernels and stuff, I recently tested a pure C program. The program is doing sort of modified ART on quite large input sets of data. So the code executes some FFTs and consumes quite some time to finish calculation. I can't currently post / link to any source code as this is ongoing research that cannot be published. If you're not familiar with ART, just a simple explanation what it does. ART is a technique used to reconstruct the data received from a computer tomograph machine to get visible images for diagnosis. So our version of the code reconstructs data sets of sizes like 2048x2048x512. Up until now, nothing too special nor rocket science involved. After some hours of debugging and fixing errors, the code was tested on reference results and we can confirm the code works as it is supposed to. The only library the code is using is standard math.h . No special compile parameters, no additional library stuff that might bring in additional problems.

Observing the problem

The code implements ART using a technique to minimize the projections needed for reconstructing the data. So let's assume we can reconstruct one slice of data involving 25 projections. The code is started with exactly the same input data on 12 cores. Please note that the implementation is not based on multithreading, currently 12 instances of the program are launched. I know this isn't the best way to do it, involving proper thread management is heavily advised and this is already on the list of improvements :)

So when we run at least two instances of the program (every instance working on a separate data slice), the results are of some projections are wrong in a random fashion. To give you an idea of the results, please see Table1. Please note that the input data is always the same.

Running only one instance of the code involving one core of the CPU, the results are all correct. Even performing some runs involving one CPU core, the results remain correct. Only involving at least two or more cores generates a result pattern as seen in Table1.

Identifying the problem

Okay this took quite some hours to get an idea of what is actually going wrong. So we went through the whole code, most of those problems begin with a minor implementation mistake. But, well, no (of course we cannot proof the absence of bugs nor guarantee it). To verify our code, we used two different machines:

(Machine1) Intel Core i5 Quad-Core (Model from late 2009)
(Machine2) Virtual Machine running on Intel XEON 6core SandyBridge CPU

surprisingly, both Machine1 & Machine2 produce always correct results. Even using all CPU-cores, the results remain correct. Not even one wrong result in over 50 runs on every machine. Code was compiled on every target machine without optimization options or any specific compiler settings. So, reading the news led to the following findings:

So the folks over at Prime95 and the Mersenne Community seem to be the first ones to discover and identify this nasty bug. The referenced postings and news support the suspicion, that the problem only exists under heavy workload. Following my observation, I can confirm this behavior.

The question(s)

Have you / the community observed this problem on Haswell CPUs as well as on Skylake CPUs?
As gcc does per default AVX(2) optimization (whenever possible), turning off this optimization would help?
How can I compile my code and ensure, that any optimization that might be affected by this bug is turned off? So far I read only about a problem using the AVX2 command set in Haswell / Skylake architectures.

Solutions?

Okay I can turn off all AVX2 optimizations. But this slows down my code. Intel might release a BIOS update to mainboard manufactures that would modify the microcode in Intel CPUs. As it seems to be a hardware bug, this might become interesting even by updating the CPUs microcode. I think it might be a valid option, as Intel CPUs use some RISC to CISC translation mechanisms controlled by Microcode.

EDIT: Techreport.com - Errata prompts Intel to disable TSX in Haswell, early Broadwell CPUs Will check the microcode version in my CPU.

EDIT2: As of now (19.01.2016 15:39 CET) Memtest86+ v4.20 is running and testing the memory. As this seems to take quite some time to finish, I'll update the post tomorrow with results.

EDIT3: As of now (21.01.2016 09:35 CET) Memtest86+ finished two runs and passed. Not even one memory error. Updated the microcode of the CPU from revision=0x2d to revision=0x36. Currently preparing source code for releasing here. Problem with the wrong results consists. As I'm not the author of the code in question, I have to double check not to post code I'm not allowed to. I'm also using the workstation and maintaining it.

EDIT4: (22.01.2016) (12:15 CET) Here ist the Makefile used to compile the sourcecode:

# VARIABLES ==================================================================
CC = gcc
CFLAGS = --std=c99 -Wall
#LDFLAGS = -lm -lgomp   -fast -s -m64 
LDFLAGS = -lm 

OBJ = ArtReconstruction2Min.o


# RULES AND DEPENDENCIES ====================================================

# linking all object files
all: $(OBJ)
  
    $(CC) -o ART2Min $(OBJ) $(LDFLAGS)         

    
# every o-file depends on the corresonding c-file, -g Option bedeutet Debugging Informationene setzen
%.o: %.c
    $(CC)  -c -g $<  $(CFLAGS)
  
    
# MAKE CLEAN =================================================================
clean: 
    rm -f *.o
    rm -f main

and the gcc -v output:

gcc -v
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/4.9/lto-wrapper
Target: x86_64-linux-gnu
Configured with: ../src/configure -v --with-pkgversion='Ubuntu 4.9.2-10ubuntu13' --with-bugurl=file:///usr/share/doc/gcc-4.9/README.Bugs --enable-languages=c,c++,java,go,d,fortran,objc,obj-c++ --prefix=/usr --program-suffix=-4.9 --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --with-gxx-include-dir=/usr/include/c++/4.9 --libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-gnu-unique-object --disable-vtable-verify --enable-plugin --with-system-zlib --disable-browser-plugin --enable-java-awt=gtk --enable-gtk-cairo --with-java-home=/usr/lib/jvm/java-1.5.0-gcj-4.9-amd64/jre --enable-java-home --with-jvm-root-dir=/usr/lib/jvm/java-1.5.0-gcj-4.9-amd64 --with-jvm-jar-dir=/usr/lib/jvm-exports/java-1.5.0-gcj-4.9-amd64 --with-arch-directory=amd64 --with-ecj-jar=/usr/share/java/eclipse-ecj.jar --enable-objc-gc --enable-multiarch --disable-werror --with-arch-32=i686 --with-abi=m64 --with-multilib-list=m32,m64,mx32 --enable-multilib --with-tune=generic --enable-checking=release --build=x86_64-linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu
Thread model: posix
gcc version 4.9.2 (Ubuntu 4.9.2-10ubuntu13)

Why the downvotes? This is a great, valid question! I will try to reproduce in a equivalent setup. — rzo1
@specializt well, As his tests shows that 11 of 12 of those identically cores are NOT doing the same thing, despite the fact that they should be doing gives this setup some real sense. Having sporadic failures when calculating it is quite a task to come up with such a "dumb" thing to do, to reveal that some of the basic preassumptions (the code will be behaving identically for identic input under any load on any core) is false. — DThought
The fact that he may or may not have discovered either a hardware bug (very unlikely) or a hardware defect (very likely) via senseless, redundant operations does not make the approach any smarter. What he currently experiences is called "luck" - he would've also discovered the same problem(s) with CPU-intensive testing tools like IBT or prime95 with days of runtime. @semm0 : download and run IBT - if your machine locks up you know that the problem is either related to thermal dissipation or even a hardware defect - sporadic calculation errors are pretty common in both cases. — specializt
"No special compile parameters". How do you know? What are you compile options? You say "As gcc does per default AVX(2) optimization". No it does not. It only uses SSE2 by default in 64-bit mode. You must have added some options. You ask "turning off this optimization would help?" Why don't you test it? Again, state your compile options and also your compiler and version. — Z boson
Does your code use any global state variable? If so then even if multiple threads run the same function and if they write to the global state variable this could give the wrong result. — Z boson

semm0 semm0 · Accepted Answer · 2016-01-22T14:52:23

EDIT: Problem solved. I have to shout out a huge Sorry to the community and a big thank you for your hints. Sorry to user anonymous, who seems to be involved into kernel development. What happened? We spent another 2 days debugging and fiddling around with the program code. No implementation problems were found. BUT: the main code involves another helper program. This helper program calculates weights for the ART algorithm on demand. So after debugging and testing, this helper program messed up, when running at least 4 processes. So this was NOT a Kernel / hardware problem, but a software (memory access) problem.

Lessons learned:

Debug every tool that is involved into the calculation process.
Microcode was outdated. SuperMicro is informed about this.
Ubuntu 15.04 possibly needs additional tools, so that all Cores of the CPU run at full speed. Achieved this by installing Ubuntu 14.04 - all cores running at 2,5GHz.
I need to spent some beer if we ever meet up at a conference.

So after three days of thinking, testing and fiddling around with the machine, I discovered the following observations today:

Ubuntu 15.04 runs the CPU with 420 - 650 MHz per Core. Okay I thought this is an Energy-saving option, so I followed various guides to set the speed to the maximum (2.50 GHz). It didn't work. Checked with cpufreq-utils.
Results still remained wrong after several tests on this machine. Other (i5, i7, XEON) machines produced correct results.
I read that other users experienced issues with Ubuntu 15.04 and the CPU frequency. So I decided to plug in a SSD and install Ubuntu 14.04. Checked again what the CPU frequency is now.. and it showed 2.50 GHz as I expected it.
Again started the reconstruction algorithm (which was now like 4-5 times faster than on Ubuntu 15.04) and waited for the results. Okay. Results are correct now! I double checked, started 9 processes and compared results. Still correct.

So I can only assume that there might be a problem in Ubuntu 15.04 / kernel using Speedstep in this CPU. CPU in 15.04 ran all the time between 420 - 650 MHz, while the min CPU speed is expected to be 1,20 GHz and the max CPU speed is 3,30 GHz. If somebody wants the check, I can offer the source code and example data leading to this problem.

Sorry for suspecting this be a CPU bug.

EDIT: after some more testing, the problem is only solved for some scenarios but not yet for all. I'll do more testing.