CPU build options#

Description#

The following options are mainly used to change the default behavior of optimizations that target certain CPU features:

  • --cpu-baseline: minimal set of required CPU features.

    Default value is min which provides the minimum CPU features that can safely run on a wide range of platforms within the processor family.

    Note

    During the runtime, NumPy modules will fail to load if any of specified features are not supported by the target CPU (raises Python runtime error).

  • --cpu-dispatch: dispatched set of additional CPU features.

    Default value is max -xop -fma4 which enables all CPU features, except for AMD legacy features (in case of X86).

    Note

    During the runtime, NumPy modules will skip any specified features that are not available in the target CPU.

These options are accessible through distutils commands distutils.command.build, distutils.command.build_clib and distutils.command.build_ext. They accept a set of CPU features or groups of features that gather several features or special options that perform a series of procedures.

Note

If build_clib or build_ext are not specified by the user, the arguments of build will be used instead, which also holds the default values.

To customize both build_ext and build_clib:

cd /path/to/numpy
python setup.py build --cpu-baseline="avx2 fma3" install --user

To customize only build_ext:

cd /path/to/numpy
python setup.py build_ext --cpu-baseline="avx2 fma3" install --user

To customize only build_clib:

cd /path/to/numpy
python setup.py build_clib --cpu-baseline="avx2 fma3" install --user

You can also customize CPU/build options through PIP command:

pip install --no-use-pep517 --global-option=build \
--global-option="--cpu-baseline=avx2 fma3" \
--global-option="--cpu-dispatch=max" ./

Quick Start#

In general, the default settings tend to not impose certain CPU features that may not be available on some older processors. Raising the ceiling of the baseline features will often improve performance and may also reduce binary size.

The following are the most common scenarios that may require changing the default settings:

I am building NumPy for my local use#

And I do not intend to export the build to other users or target a different CPU than what the host has.

Set native for baseline, or manually specify the CPU features in case of option native isn’t supported by your platform:

python setup.py build --cpu-baseline="native" bdist

Building NumPy with extra CPU features isn’t necessary for this case, since all supported features are already defined within the baseline features:

python setup.py build --cpu-baseline=native --cpu-dispatch=none bdist

Note

A fatal error will be raised if native isn’t supported by the host platform.

I do not want to support the old processors of the x86 architecture#

Since most of the CPUs nowadays support at least AVX, F16C features, you can use:

python setup.py build --cpu-baseline="avx f16c" bdist

Note

--cpu-baseline force combine all implied features, so there’s no need to add SSE features.

I’m facing the same case above but with ppc64 architecture#

Then raise the ceiling of the baseline features to Power8:

python setup.py build --cpu-baseline="vsx2" bdist

Having issues with AVX512 features?#

You may have some reservations about including of AVX512 or any other CPU feature and you want to exclude from the dispatched features:

python setup.py build --cpu-dispatch="max -avx512f -avx512cd \
-avx512_knl -avx512_knm -avx512_skx -avx512_clx -avx512_cnl -avx512_icl" \
bdist

Supported Features#

The names of the features can express one feature or a group of features, as shown in the following tables supported depend on the lowest interest:

Note

The following features may not be supported by all compilers, also some compilers may produce different set of implied features when it comes to features like AVX512, AVX2, and FMA3. See Platform differences for more details.

On x86#

Name

Implies

Gathers

SSE

SSE2

SSE2

SSE

SSE3

SSE SSE2

SSSE3

SSE SSE2 SSE3

SSE41

SSE SSE2 SSE3 SSSE3

POPCNT

SSE SSE2 SSE3 SSSE3 SSE41

SSE42

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT

AVX

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42

XOP

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX

FMA4

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX

F16C

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX

FMA3

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C

AVX2

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C

AVX512F

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2

AVX512CD

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F

AVX512_KNL

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD

AVX512ER AVX512PF

AVX512_KNM

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_KNL

AVX5124FMAPS AVX5124VNNIW AVX512VPOPCNTDQ

AVX512_SKX

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD

AVX512VL AVX512BW AVX512DQ

AVX512_CLX

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_SKX

AVX512VNNI

AVX512_CNL

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_SKX

AVX512IFMA AVX512VBMI

AVX512_ICL

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_SKX AVX512_CLX AVX512_CNL

AVX512VBMI2 AVX512BITALG AVX512VPOPCNTDQ

AVX512_SPR

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_SKX AVX512_CLX AVX512_CNL AVX512_ICL

AVX512FP16

On IBM/POWER big-endian#

Name

Implies

VSX

VSX2

VSX

VSX3

VSX VSX2

VSX4

VSX VSX2 VSX3

On IBM/POWER little-endian#

Name

Implies

VSX

VSX2

VSX2

VSX

VSX3

VSX VSX2

VSX4

VSX VSX2 VSX3

On ARMv7/A32#

Name

Implies

NEON

NEON_FP16

NEON

NEON_VFPV4

NEON NEON_FP16

ASIMD

NEON NEON_FP16 NEON_VFPV4

ASIMDHP

NEON NEON_FP16 NEON_VFPV4 ASIMD

ASIMDDP

NEON NEON_FP16 NEON_VFPV4 ASIMD

ASIMDFHM

NEON NEON_FP16 NEON_VFPV4 ASIMD ASIMDHP

On ARMv8/A64#

Name

Implies

NEON

NEON_FP16 NEON_VFPV4 ASIMD

NEON_FP16

NEON NEON_VFPV4 ASIMD

NEON_VFPV4

NEON NEON_FP16 ASIMD

ASIMD

NEON NEON_FP16 NEON_VFPV4

ASIMDHP

NEON NEON_FP16 NEON_VFPV4 ASIMD

ASIMDDP

NEON NEON_FP16 NEON_VFPV4 ASIMD

ASIMDFHM

NEON NEON_FP16 NEON_VFPV4 ASIMD ASIMDHP

On IBM/ZSYSTEM(S390X)#

Name

Implies

VX

VXE

VX

VXE2

VX VXE

Special Options#

  • NONE: enable no features.

  • NATIVE: Enables all CPU features that supported by the host CPU, this operation is based on the compiler flags (-march=native, -xHost, /QxHost)

  • MIN: Enables the minimum CPU features that can safely run on a wide range of platforms:

    For Arch

    Implies

    x86 (32-bit mode)

    SSE SSE2

    x86_64

    SSE SSE2 SSE3

    IBM/POWER (big-endian mode)

    NONE

    IBM/POWER (little-endian mode)

    VSX VSX2

    ARMHF

    NONE

    ARM64 A.K. AARCH64

    NEON NEON_FP16 NEON_VFPV4 ASIMD

    IBM/ZSYSTEM(S390X)

    NONE

  • MAX: Enables all supported CPU features by the compiler and platform.

  • Operators-/+: remove or add features, useful with options MAX, MIN and NATIVE.

Behaviors#

  • CPU features and other options are case-insensitive, for example:

    python setup.py build --cpu-dispatch="SSE41 avx2 FMA3"
    
  • The order of the requested optimizations doesn’t matter:

    python setup.py build --cpu-dispatch="SSE41 AVX2 FMA3"
    # equivalent to
    python setup.py build --cpu-dispatch="FMA3 AVX2 SSE41"
    
  • Either commas or spaces or ‘+’ can be used as a separator, for example:

    python setup.py build --cpu-dispatch="avx2 avx512f"
    # or
    python setup.py build --cpu-dispatch=avx2,avx512f
    # or
    python setup.py build --cpu-dispatch="avx2+avx512f"
    

    all works but arguments should be enclosed in quotes or escaped by backslash if any spaces are used.

  • --cpu-baseline combines all implied CPU features, for example:

    python setup.py build --cpu-baseline=sse42
    # equivalent to
    python setup.py build --cpu-baseline="sse sse2 sse3 ssse3 sse41 popcnt sse42"
    
  • --cpu-baseline will be treated as “native” if compiler native flag -march=native or -xHost or /QxHost is enabled through environment variable CFLAGS:

    export CFLAGS="-march=native"
    python setup.py install --user
    # is equivalent to
    python setup.py build --cpu-baseline=native install --user
    
  • --cpu-baseline escapes any specified features that aren’t supported by the target platform or compiler rather than raising fatal errors.

    Note

    Since --cpu-baseline combines all implied features, the maximum supported of implied features will be enabled rather than escape all of them. For example:

    # Requesting `AVX2,FMA3` but the compiler only support **SSE** features
    python setup.py build --cpu-baseline="avx2 fma3"
    # is equivalent to
    python setup.py build --cpu-baseline="sse sse2 sse3 ssse3 sse41 popcnt sse42"
    
  • --cpu-dispatch does not combain any of implied CPU features, so you must add them unless you want to disable one or all of them:

    # Only dispatches AVX2 and FMA3
    python setup.py build --cpu-dispatch=avx2,fma3
    # Dispatches AVX and SSE features
    python setup.py build --cpu-baseline=ssse3,sse41,sse42,avx,avx2,fma3
    
  • --cpu-dispatch escapes any specified baseline features and also escapes any features not supported by the target platform or compiler without raising fatal errors.

Eventually, you should always check the final report through the build log to verify the enabled features. See Build report for more details.

Platform differences#

Some exceptional conditions force us to link some features together when it come to certain compilers or architectures, resulting in the impossibility of building them separately.

These conditions can be divided into two parts, as follows:

Architectural compatibility

The need to align certain CPU features that are assured to be supported by successive generations of the same architecture, some cases:

  • On ppc64le VSX(ISA 2.06) and VSX2(ISA 2.07) both imply one another since the first generation that supports little-endian mode is Power-8`(ISA 2.07)`

  • On AArch64 NEON NEON_FP16 NEON_VFPV4 ASIMD implies each other since they are part of the hardware baseline.

For example:

# On ARMv8/A64, specify NEON is going to enable Advanced SIMD
# and all predecessor extensions
python setup.py build --cpu-baseline=neon
# which equivalent to
python setup.py build --cpu-baseline="neon neon_fp16 neon_vfpv4 asimd"

Note

Please take a deep look at Supported Features, in order to determine the features that imply one another.

Compilation compatibility

Some compilers don’t provide independent support for all CPU features. For instance Intel’s compiler doesn’t provide separated flags for AVX2 and FMA3, it makes sense since all Intel CPUs that comes with AVX2 also support FMA3, but this approach is incompatible with other x86 CPUs from AMD or VIA.

For example:

# Specify AVX2 will force enables FMA3 on Intel compilers
python setup.py build --cpu-baseline=avx2
# which equivalent to
python setup.py build --cpu-baseline="avx2 fma3"

The following tables only show the differences imposed by some compilers from the general context that been shown in the Supported Features tables:

Note

Features names with strikeout represent the unsupported CPU features.

On x86::Intel Compiler#

Name

Implies

Gathers

FMA3

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C AVX2

AVX2

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3

AVX512F

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512CD

XOP

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX

FMA4

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX

AVX512_SPR

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_SKX AVX512_CLX AVX512_CNL AVX512_ICL

AVX512FP16

On x86::Microsoft Visual C/C++#

Name

Implies

Gathers

FMA3

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C AVX2

AVX2

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3

AVX512F

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512CD AVX512_SKX

AVX512CD

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512_SKX

AVX512_KNL

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD

AVX512ER AVX512PF

AVX512_KNM

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_KNL

AVX5124FMAPS AVX5124VNNIW AVX512VPOPCNTDQ

AVX512_SPR

SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_SKX AVX512_CLX AVX512_CNL AVX512_ICL

AVX512FP16

Build report#

In most cases, the CPU build options do not produce any fatal errors that lead to hanging the build. Most of the errors that may appear in the build log serve as heavy warnings due to the lack of some expected CPU features by the compiler.

So we strongly recommend checking the final report log, to be aware of what kind of CPU features are enabled and what are not.

You can find the final report of CPU optimizations at the end of the build log, and here is how it looks on x86_64/gcc:

########### EXT COMPILER OPTIMIZATION ###########
Platform      :
  Architecture: x64
  Compiler    : gcc

CPU baseline  :
  Requested   : 'min'
  Enabled     : SSE SSE2 SSE3
  Flags       : -msse -msse2 -msse3
  Extra checks: none

CPU dispatch  :
  Requested   : 'max -xop -fma4'
  Enabled     : SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_KNL AVX512_KNM AVX512_SKX AVX512_CLX AVX512_CNL AVX512_ICL
  Generated   :
              :
  SSE41       : SSE SSE2 SSE3 SSSE3
  Flags       : -msse -msse2 -msse3 -mssse3 -msse4.1
  Extra checks: none
  Detect      : SSE SSE2 SSE3 SSSE3 SSE41
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_arithmetic.dispatch.c
              : numpy/core/src/umath/_umath_tests.dispatch.c
              :
  SSE42       : SSE SSE2 SSE3 SSSE3 SSE41 POPCNT
  Flags       : -msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2
  Extra checks: none
  Detect      : SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42
              : build/src.linux-x86_64-3.9/numpy/core/src/_simd/_simd.dispatch.c
              :
  AVX2        : SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C
  Flags       : -msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mavx2
  Extra checks: none
  Detect      : AVX F16C AVX2
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_arithm_fp.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_arithmetic.dispatch.c
              : numpy/core/src/umath/_umath_tests.dispatch.c
              :
  (FMA3 AVX2) : SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C
  Flags       : -msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2
  Extra checks: none
  Detect      : AVX F16C FMA3 AVX2
              : build/src.linux-x86_64-3.9/numpy/core/src/_simd/_simd.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_exponent_log.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_trigonometric.dispatch.c
              :
  AVX512F     : SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2
  Flags       : -msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f
  Extra checks: AVX512F_REDUCE
  Detect      : AVX512F
              : build/src.linux-x86_64-3.9/numpy/core/src/_simd/_simd.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_arithm_fp.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_arithmetic.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_exponent_log.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_trigonometric.dispatch.c
              :
  AVX512_SKX  : SSE SSE2 SSE3 SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD
  Flags       : -msse -msse2 -msse3 -mssse3 -msse4.1 -mpopcnt -msse4.2 -mavx -mf16c -mfma -mavx2 -mavx512f -mavx512cd -mavx512vl -mavx512bw -mavx512dq
  Extra checks: AVX512BW_MASK AVX512DQ_MASK
  Detect      : AVX512_SKX
              : build/src.linux-x86_64-3.9/numpy/core/src/_simd/_simd.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_arithmetic.dispatch.c
              : build/src.linux-x86_64-3.9/numpy/core/src/umath/loops_exponent_log.dispatch.c
CCompilerOpt.cache_flush[804] : write cache to path -> /home/seiko/work/repos/numpy/build/temp.linux-x86_64-3.9/ccompiler_opt_cache_ext.py

########### CLIB COMPILER OPTIMIZATION ###########
Platform      :
  Architecture: x64
  Compiler    : gcc

CPU baseline  :
  Requested   : 'min'
  Enabled     : SSE SSE2 SSE3
  Flags       : -msse -msse2 -msse3
  Extra checks: none

CPU dispatch  :
  Requested   : 'max -xop -fma4'
  Enabled     : SSSE3 SSE41 POPCNT SSE42 AVX F16C FMA3 AVX2 AVX512F AVX512CD AVX512_KNL AVX512_KNM AVX512_SKX AVX512_CLX AVX512_CNL AVX512_ICL
  Generated   : none

There is a separate report for each of build_ext and build_clib that includes several sections, and each section has several values, representing the following:

Platform:

  • Architecture: The architecture name of target CPU. It should be one of x86, x64, ppc64, ppc64le, armhf, aarch64, s390x or unknown.

  • Compiler: The compiler name. It should be one of gcc, clang, msvc, icc, iccw or unix-like.

CPU baseline:

  • Requested: The specific features and options to --cpu-baseline as-is.

  • Enabled: The final set of enabled CPU features.

  • Flags: The compiler flags that were used to all NumPy C/C++ sources during the compilation except for temporary sources that have been used for generating the binary objects of dispatched features.

  • Extra checks: list of internal checks that activate certain functionality or intrinsics related to the enabled features, useful for debugging when it comes to developing SIMD kernels.

CPU dispatch:

  • Requested: The specific features and options to --cpu-dispatch as-is.

  • Enabled: The final set of enabled CPU features.

  • Generated: At the beginning of the next row of this property, the features for which optimizations have been generated are shown in the form of several sections with similar properties explained as follows:

    • One or multiple dispatched feature: The implied CPU features.

    • Flags: The compiler flags that been used for these features.

    • Extra checks: Similar to the baseline but for these dispatched features.

    • Detect: Set of CPU features that need be detected in runtime in order to execute the generated optimizations.

    • The lines that come after the above property and end with a ‘:’ on a separate line, represent the paths of c/c++ sources that define the generated optimizations.

Runtime dispatch#

Importing NumPy triggers a scan of the available CPU features from the set of dispatchable features. This can be further restricted by setting the environment variable NPY_DISABLE_CPU_FEATURES to a comma-, tab-, or space-separated list of features to disable. This will raise an error if parsing fails or if the feature was not enabled. For instance, on x86_64 this will disable AVX2 and FMA3:

NPY_DISABLE_CPU_FEATURES="AVX2,FMA3"

If the feature is not available, a warning will be emitted.