llvm dev - May 2019 - [cfe-dev] [RFC] Expose user provided vector function for auto-vectorization.

Dear all,

This RFC is a proposal to provide auto-vectorization functionality for user
provided vector functions.

The proposal is a modification of an RFC that I have sent out a couple of months
ago, with the title `[RFC] Re-implementing -fveclib with OpenMP` (see
http://lists.llvm.org/pipermail/llvm-dev/2018-December/128426.html). The
previous RFC is to be considered abandoned.

The original RFC was proposing to re-implement the `-fveclib` command line
option. This proposal avoids that, and limits its scope to the mechanics of
providing vector function in user code that the compiler can pick up for
auto-vectorization. This narrower scope limits the impact of changes that are
needed in both clang and LLVM.

Please let me know what you think.

Kind regards,

Francesco


================================================================================
Introduction
===========
This RFC encompasses the proposal of informing the vectorizer about the
availability of vector functions provided by the user. The mechanism is
based on the use of the directive `declare variant` introduced in OpenMP
5.0 [^1].

The mechanism proposed has the following properties:

1.  Decouples the compiler front-end that knows about the availability
    of vectorized routines, from the back-end that knows how to make use
    of them.
2.  Enable support for a developer's own vector libraries without
    requiring changes to the compiler.
3.  Enables other frontends (e.g. f18) to add scalar-to-vector function
    mappings as relevant for their own runtime libraries, etc.

The implemetation consists of two separate sets of changes.

The first set is a set o changes in `llvm`, and consists of:

1.  [Changes in LLVM IR](#llvmIR) to provide information about the
    availability of user-defined vector functions via metadata attached
    to an `llvm::CallInst`.
2.  [An infrastructure](#infrastructure) that can be queried to retrive
    information about the available vector functions associated to a
    `llvm::CallInst`.
3.  [Changes in the LoopVectorizer](#LV) to use the API to query the
    metadata.

The second set consists of the changes [changes in clang](#clang) that
are needed too to recognize the `#pragma clang declare variant`
directive.

Proposed changes
===============
We propose an implementation that uses `#pragma clang declare variant`
to inform the backend components about the availability of vector
version of scalar functions found in IR. The mechanism relies in storing
such information in IR metadata, and therefore makes the
auto-vectorization of function calls a mid-end (`opt`) process that is
independent on the front-end that generated such IR metadata.

This implementation provides a generic mechanism that the users of the
LLVM compiler will be able to use for interfacing their own vector
routines for generic code.

The implementation can also expose vectorization-specific descriptors --
for example, like the `linear` and `uniform` clauses of the OpenMP
`declare simd` directive -- that could be used to finely tune the
automatic vectorization of some functions (think for example the
vectorization of `double sincos(double , double *, double *)`, where
`linear` can be used to give extra information about the memory layout
of the 2 pointers parameters in the vector version).

The directive `#pragma clang declare variant` follows the syntax of the
`#pragma omp declare variant` directive of OpenMP.

We define the new directive in the `clang` namespace instead of using
the `omp` one of OpenMP to allow the compiler to perform
auto-vectorization outside of an OpenMP SIMD context.

The mechanism is base on OpenMP to provide a uniform user experience
across the two mechanism, and to maximise the number of shared
components of the infrastructure needed in the compiler frontend to
enable the feature.

Changes in LLVM IR {#llvmIR}
------------------

The IR is enriched with metadata that details the availability of vector
versions of an associated scalar function. This metadata is attached to
the call site of the scalar function.

The metadata takes the form of an attribute containing a comma separated
list of vector function mappings. Each entry has a unique name that
follows the Vector Function ABI[^2] and real name that is used when
generating calls to this vector function.

    vfunc_name1(real_name1), vfunc_name2(real_name2)

The Vector Function ABI name describes the signature of the vector
function so that properties like vectorisation factor can be queried
during compilation.

The `(real name)` token is optional and assumed to match the Vector
Function ABI name when omitted.

For example, the availability of a 2-lane double precision `sin`
function via SVML when targeting AVX on x86 is provided by the following
IR.

    // ...
    ... = call double @sin(double) #0
    // ...

    #0 = { vector-variant = {"_ZGVcN2v_sin(__svml_sin2),
                              _ZGVdN4v_sin(__svml_sin4),
                              ..."} }

The string `"_ZGVcN2v_sin(__svml_sin2)"` in this vector-variant
attribute provides information on the shape of the vector function via
the string `_ZGVcN2v_sin`, mangled according to the Vector Function ABI
for Intel, and remaps the standard Vector Function ABI name to the
non-standard name `__svml_sin2`.

This metadata is compatible with the proposal "Proposal for function
vectorization and loop vectorization with function calls",[^3] that uses
Vector Function ABI mangled names to inform the vectorizer about the
availability of vector functions. The proposal extends the original by
allowing the explicit mapping of the Vector Function ABI mangled name to
a non-standard name, which allows the use of existing vector libraries.

The `vector-variant` attribute needs to be attached on a per-call basis
to avoid conflicts when merging modules with different vector variants.

The query infrastructure: SVFS {#infrastructure}
------------------------------

The Search Vector Function System (SVFS) is constructed from an
`llvm::Module` instance so it can create function definitions. The SVFS
exposes an API with two methods.

### `SVFS::isFunctionVectorizable`

This method queries the avilability of a vectorized version of a
function. The signature of the method is as follows.

    bool isFunctionVectorizable(llvm::CallInst * Call, ParTypeMap Params);

The method determine the availability of vector version of the function
invoked by the `Call` parameter by looking at the `vector-variant`
metadata.

The `Params` argument is a map that associates the position of a
parameter in the `CallInst` to its `ParameterType` descriptor. The
`ParameterType` descriptor holds information about the shape of the
correspondend parameter in the signature of the vector function. This
`ParamaterType` is used to query the SVMS about the availability of
vector version that have `linear`, `uniform` or `align` parameters (in
the sense of OpenMP 4.0 and onwards).

The method `isFunctionVectorizable`, when invoked with an empty
`ParTypeMap`, is equivalent to the `TargetLibraryInfo` method
`isFunctionVectorizable(StrinRef Name)`.

### `SVFS::getVectorizedFunction`

This method returns the vector function declaration that correspond to
the needs of the vectorization technique that is being run.

The signature of the function is as follows.

    std::pair<llvm::FunctionType *, std::string> getVectorizedFunction(
      llvm::CallInst * Call, unsigned VF, bool IsMasked, ParTypeSet Params);

The `Call` parameter is the call instance that is being vectorized, the
`VF` parameter represent the vectorization factor (how many lanes), the
`IsMasked` parameter decides whether or not the signature of the vector
function is required to have a mask parameter, the `Params` parameter
describes the shape of the vector function as in the
`isFunctionVectorizable` method.

The methods uses the `vector-variant` metadata and returns the function
signature and the name of the function based on the input parameters.

The SVFS can add new function definitions, in the same module as the
`Call`, to provide vector functions that are not present within the
vector-variant metadata. For example, if a library provides a vector
version of a function with a vectorization factor of 2, but the
vectorizer is requesting a vectorization factor of 4, the SVFS is
allowed to create a definition that calls the 2-lane version twice. This
capability applies similarly for providing masked and unmasked versions
when the request does not match what is available in the library.

This method is equivalent to the TLI method
`StringRef getVectorizedFunction(StringRef F, unsigned VF) const;`.

Notice that to fully support OpenMP vectorization we need to think about
a fuzzy matching mechanism that is able to select a candidate in the
calling context. However, this proposal is intended for scalar-to-vector
mappings of math-like functions that are most likely to associate a
unique vector candidate in most contexts. Therefore, extending this
behavior to a generic one is an aspect of the implementation that will
be treated in a separate RFC about the vectorization pass.

### Scalable vectorization

Both methods of the SVFS API will be extended with a boolean parameter
to specify whether scalable signatures are needed by the user of the
SVFS.

Changes in clang {#clang}
----------------

We use clang to generate the metadata described above.

In the compilation unit, the vector function definition or declaration
must be visible and associated to the scalar version via the
`#pragma clang declare variant` according to the rule defined by the
correspondent `#pragma omp declare variant` defined in OpenMP 5.0, as in
the following example.

    #pragma clang declare variant(vector_sinf) \
    match(construct=simd(simdlen(4),notinbranch),
device={isa("simd")})
    extern float sinf(float);

    float32x4_t vector_sinf(float32x4_t x);

The `construct` set in the directive, together with the `device` set, is
used to generate the vector mangled name to be used in the
`vector-variant` attribute, for example `_ZGVnN2v_sin`, when targeting
AArch64 Advanced SIMD code generation. The rule for mangling the name of
the scalar function in the vector name are defined in the the Vector
Function ABI specification of the target.

The part of the vector-variant attribute that redirects the call to
`vector_sinf` is derived from the `variant-id` specified in the
`variant` clause.

Summary
======
New `clang` directive in clang
------------------------------

`#pragma omp declare variant`, same as `#pragma omp declare variant`
restricted to the `simd` context selector, from OpenMP 5.0+.

Option behavior, and interaction with OpenMP
--------------------------------------------

The behavior described below makes sure that
`#pragma cland declare variant` function vectorization and OpenMP
function vectorization are orthogonal.

`-fclang-declare-variant`

:   The `#pragma clang declare variant` directives are parsed and used
    to populate the `vector-variant` attribute.

`-fopenmp[-simd]`

:   The `#pragma omp declare variant` directives are parsed and used to
    populate the `vector-variant` attribute.

`-fopenmp[-simd]`and `-fno-clang-declare-variant`

:   The directive `#pragma omp declare variant` is used to populate the
    `vector-variant` attribute in IR. The directive
    `#pragma   clang declare variant` are ignored.

[^1]:
<https://www.openmp.org/wp-content/uploads/OpenMP-API-Specification-5.0.pdf>

[^2]: Vector Function ABI for x86:
    <https://software.intel.com/en-us/articles/vector-simd-function-abi>.
    Vector Function ABI for AArch64:
   
https://developer.arm.com/products/software-development-tools/hpc/arm-compiler-for-hpc/vector-function-abi

[^3]: <http://lists.llvm.org/pipermail/cfe-dev/2016-March/047732.html>

I generally like the idea of having support in IR for vectorization of
custom functions.  I have several use cases which would benefit from this.

I'd suggest a couple of reframings to the IR representation though.

First, this should probably be specified as metadata/attribute on a
function declaration.  Allowing the callsite variant is fine, but it
should primarily be a property of the called function, not of the call
site.  Being able to specify it once per declaration is much cleaner.

Second, I really don't like the mangling use here.  We need a better way
to specify the properties of the function then it's mangled name.  One
thought to explore is to directly use the Value of the function
declaration (since this is metadata and we can do that), and then tie
the properties to the function declaration in some way?  Sorry, I don't
really have a specific suggestion here.

Philip

On 5/28/19 12:44 PM, Francesco Petrogalli via llvm-dev
wrote:
> Dear all,
>
> This RFC is a proposal to provide auto-vectorization functionality for user
provided vector functions.
>
> The proposal is a modification of an RFC that I have sent out a couple of
months ago, with the title `[RFC] Re-implementing -fveclib with OpenMP` (see
http://lists.llvm.org/pipermail/llvm-dev/2018-December/128426.html). The
previous RFC is to be considered abandoned.
>
> The original RFC was proposing to re-implement the `-fveclib` command line
option. This proposal avoids that, and limits its scope to the mechanics of
providing vector function in user code that the compiler can pick up for
auto-vectorization. This narrower scope limits the impact of changes that are
needed in both clang and LLVM.
>
> Please let me know what you think.
>
> Kind regards,
>
> Francesco
>
>
>
================================================================================>
> Introduction
> ===========>
> This RFC encompasses the proposal of informing the vectorizer about the
> availability of vector functions provided by the user. The mechanism is
> based on the use of the directive `declare variant` introduced in OpenMP
> 5.0 [^1].
>
> The mechanism proposed has the following properties:
>
> 1.  Decouples the compiler front-end that knows about the availability
>     of vectorized routines, from the back-end that knows how to make use
>     of them.
> 2.  Enable support for a developer's own vector libraries without
>     requiring changes to the compiler.
> 3.  Enables other frontends (e.g. f18) to add scalar-to-vector function
>     mappings as relevant for their own runtime libraries, etc.
>
> The implemetation consists of two separate sets of changes.
>
> The first set is a set o changes in `llvm`, and consists of:
>
> 1.  [Changes in LLVM IR](#llvmIR) to provide information about the
>     availability of user-defined vector functions via metadata attached
>     to an `llvm::CallInst`.
> 2.  [An infrastructure](#infrastructure) that can be queried to retrive
>     information about the available vector functions associated to a
>     `llvm::CallInst`.
> 3.  [Changes in the LoopVectorizer](#LV) to use the API to query the
>     metadata.
>
> The second set consists of the changes [changes in clang](#clang) that
> are needed too to recognize the `#pragma clang declare variant`
> directive.
>
> Proposed changes
> ===============>
> We propose an implementation that uses `#pragma clang declare variant`
> to inform the backend components about the availability of vector
> version of scalar functions found in IR. The mechanism relies in storing
> such information in IR metadata, and therefore makes the
> auto-vectorization of function calls a mid-end (`opt`) process that is
> independent on the front-end that generated such IR metadata.
>
> This implementation provides a generic mechanism that the users of the
> LLVM compiler will be able to use for interfacing their own vector
> routines for generic code.
>
> The implementation can also expose vectorization-specific descriptors --
> for example, like the `linear` and `uniform` clauses of the OpenMP
> `declare simd` directive -- that could be used to finely tune the
> automatic vectorization of some functions (think for example the
> vectorization of `double sincos(double , double *, double *)`, where
> `linear` can be used to give extra information about the memory layout
> of the 2 pointers parameters in the vector version).
>
> The directive `#pragma clang declare variant` follows the syntax of the
> `#pragma omp declare variant` directive of OpenMP.
>
> We define the new directive in the `clang` namespace instead of using
> the `omp` one of OpenMP to allow the compiler to perform
> auto-vectorization outside of an OpenMP SIMD context.
>
> The mechanism is base on OpenMP to provide a uniform user experience
> across the two mechanism, and to maximise the number of shared
> components of the infrastructure needed in the compiler frontend to
> enable the feature.
>
> Changes in LLVM IR {#llvmIR}
> ------------------
>
> The IR is enriched with metadata that details the availability of vector
> versions of an associated scalar function. This metadata is attached to
> the call site of the scalar function.
>
> The metadata takes the form of an attribute containing a comma separated
> list of vector function mappings. Each entry has a unique name that
> follows the Vector Function ABI[^2] and real name that is used when
> generating calls to this vector function.
>
>     vfunc_name1(real_name1), vfunc_name2(real_name2)
>
> The Vector Function ABI name describes the signature of the vector
> function so that properties like vectorisation factor can be queried
> during compilation.
>
> The `(real name)` token is optional and assumed to match the Vector
> Function ABI name when omitted.
>
> For example, the availability of a 2-lane double precision `sin`
> function via SVML when targeting AVX on x86 is provided by the following
> IR.
>
>     // ...
>     ... = call double @sin(double) #0
>     // ...
>
>     #0 = { vector-variant = {"_ZGVcN2v_sin(__svml_sin2),
>                               _ZGVdN4v_sin(__svml_sin4),
>                               ..."} }
>
> The string `"_ZGVcN2v_sin(__svml_sin2)"` in this vector-variant
> attribute provides information on the shape of the vector function via
> the string `_ZGVcN2v_sin`, mangled according to the Vector Function ABI
> for Intel, and remaps the standard Vector Function ABI name to the
> non-standard name `__svml_sin2`.
>
> This metadata is compatible with the proposal "Proposal for function
> vectorization and loop vectorization with function calls",[^3] that
uses
> Vector Function ABI mangled names to inform the vectorizer about the
> availability of vector functions. The proposal extends the original by
> allowing the explicit mapping of the Vector Function ABI mangled name to
> a non-standard name, which allows the use of existing vector libraries.
>
> The `vector-variant` attribute needs to be attached on a per-call basis
> to avoid conflicts when merging modules with different vector variants.
>
> The query infrastructure: SVFS {#infrastructure}
> ------------------------------
>
> The Search Vector Function System (SVFS) is constructed from an
> `llvm::Module` instance so it can create function definitions. The SVFS
> exposes an API with two methods.
>
> ### `SVFS::isFunctionVectorizable`
>
> This method queries the avilability of a vectorized version of a
> function. The signature of the method is as follows.
>
>     bool isFunctionVectorizable(llvm::CallInst * Call, ParTypeMap Params);
>
> The method determine the availability of vector version of the function
> invoked by the `Call` parameter by looking at the `vector-variant`
> metadata.
>
> The `Params` argument is a map that associates the position of a
> parameter in the `CallInst` to its `ParameterType` descriptor. The
> `ParameterType` descriptor holds information about the shape of the
> correspondend parameter in the signature of the vector function. This
> `ParamaterType` is used to query the SVMS about the availability of
> vector version that have `linear`, `uniform` or `align` parameters (in
> the sense of OpenMP 4.0 and onwards).
>
> The method `isFunctionVectorizable`, when invoked with an empty
> `ParTypeMap`, is equivalent to the `TargetLibraryInfo` method
> `isFunctionVectorizable(StrinRef Name)`.
>
> ### `SVFS::getVectorizedFunction`
>
> This method returns the vector function declaration that correspond to
> the needs of the vectorization technique that is being run.
>
> The signature of the function is as follows.
>
>     std::pair<llvm::FunctionType *, std::string>
getVectorizedFunction(
>       llvm::CallInst * Call, unsigned VF, bool IsMasked, ParTypeSet
Params);
>
> The `Call` parameter is the call instance that is being vectorized, the
> `VF` parameter represent the vectorization factor (how many lanes), the
> `IsMasked` parameter decides whether or not the signature of the vector
> function is required to have a mask parameter, the `Params` parameter
> describes the shape of the vector function as in the
> `isFunctionVectorizable` method.
>
> The methods uses the `vector-variant` metadata and returns the function
> signature and the name of the function based on the input parameters.
>
> The SVFS can add new function definitions, in the same module as the
> `Call`, to provide vector functions that are not present within the
> vector-variant metadata. For example, if a library provides a vector
> version of a function with a vectorization factor of 2, but the
> vectorizer is requesting a vectorization factor of 4, the SVFS is
> allowed to create a definition that calls the 2-lane version twice. This
> capability applies similarly for providing masked and unmasked versions
> when the request does not match what is available in the library.
>
> This method is equivalent to the TLI method
> `StringRef getVectorizedFunction(StringRef F, unsigned VF) const;`.
>
> Notice that to fully support OpenMP vectorization we need to think about
> a fuzzy matching mechanism that is able to select a candidate in the
> calling context. However, this proposal is intended for scalar-to-vector
> mappings of math-like functions that are most likely to associate a
> unique vector candidate in most contexts. Therefore, extending this
> behavior to a generic one is an aspect of the implementation that will
> be treated in a separate RFC about the vectorization pass.
>
> ### Scalable vectorization
>
> Both methods of the SVFS API will be extended with a boolean parameter
> to specify whether scalable signatures are needed by the user of the
> SVFS.
>
> Changes in clang {#clang}
> ----------------
>
> We use clang to generate the metadata described above.
>
> In the compilation unit, the vector function definition or declaration
> must be visible and associated to the scalar version via the
> `#pragma clang declare variant` according to the rule defined by the
> correspondent `#pragma omp declare variant` defined in OpenMP 5.0, as in
> the following example.
>
>     #pragma clang declare variant(vector_sinf) \
>     match(construct=simd(simdlen(4),notinbranch),
device={isa("simd")})
>     extern float sinf(float);
>
>     float32x4_t vector_sinf(float32x4_t x);
>
> The `construct` set in the directive, together with the `device` set, is
> used to generate the vector mangled name to be used in the
> `vector-variant` attribute, for example `_ZGVnN2v_sin`, when targeting
> AArch64 Advanced SIMD code generation. The rule for mangling the name of
> the scalar function in the vector name are defined in the the Vector
> Function ABI specification of the target.
>
> The part of the vector-variant attribute that redirects the call to
> `vector_sinf` is derived from the `variant-id` specified in the
> `variant` clause.
>
> Summary
> ======>
> New `clang` directive in clang
> ------------------------------
>
> `#pragma omp declare variant`, same as `#pragma omp declare variant`
> restricted to the `simd` context selector, from OpenMP 5.0+.
>
> Option behavior, and interaction with OpenMP
> --------------------------------------------
>
> The behavior described below makes sure that
> `#pragma cland declare variant` function vectorization and OpenMP
> function vectorization are orthogonal.
>
> `-fclang-declare-variant`
>
> :   The `#pragma clang declare variant` directives are parsed and used
>     to populate the `vector-variant` attribute.
>
> `-fopenmp[-simd]`
>
> :   The `#pragma omp declare variant` directives are parsed and used to
>     populate the `vector-variant` attribute.
>
> `-fopenmp[-simd]`and `-fno-clang-declare-variant`
>
> :   The directive `#pragma omp declare variant` is used to populate the
>     `vector-variant` attribute in IR. The directive
>     `#pragma   clang declare variant` are ignored.
>
> [^1]:
<https://www.openmp.org/wp-content/uploads/OpenMP-API-Specification-5.0.pdf>
>
> [^2]: Vector Function ABI for x86:
>    
<https://software.intel.com/en-us/articles/vector-simd-function-abi>.
>     Vector Function ABI for AArch64:
>    
https://developer.arm.com/products/software-development-tools/hpc/arm-compiler-for-hpc/vector-function-abi
>
> [^3]:
<http://lists.llvm.org/pipermail/cfe-dev/2016-March/047732.html>
>
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org
> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev

On Tue, May 28, 2019 at 2:45 PM Francesco Petrogalli via llvm-dev
<llvm-dev at lists.llvm.org> wrote:
>
> Dear all,
>
> This RFC is a proposal to provide auto-vectorization functionality for user
provided vector functions.
>
> The proposal is a modification of an RFC that I have sent out a couple of
months ago, with the title `[RFC] Re-implementing -fveclib with OpenMP` (see
http://lists.llvm.org/pipermail/llvm-dev/2018-December/128426.html). The
previous RFC is to be considered abandoned.
>
> The original RFC was proposing to re-implement the `-fveclib` command line
option. This proposal avoids that, and limits its scope to the mechanics of
providing vector function in user code that the compiler can pick up for
auto-vectorization. This narrower scope limits the impact of changes that are
needed in both clang and LLVM.
>
> Please let me know what you think.
>
> Kind regards,
>
> Francesco
>
>
>
================================================================================>
> Introduction
> ===========>
> This RFC encompasses the proposal of informing the vectorizer about the
> availability of vector functions provided by the user. The mechanism is
> based on the use of the directive `declare variant` introduced in OpenMP
> 5.0 [^1].
>
> The mechanism proposed has the following properties:
>
> 1.  Decouples the compiler front-end that knows about the availability
>     of vectorized routines, from the back-end that knows how to make use
>     of them.
> 2.  Enable support for a developer's own vector libraries without
>     requiring changes to the compiler.
> 3.  Enables other frontends (e.g. f18) to add scalar-to-vector function
>     mappings as relevant for their own runtime libraries, etc.
There is no way to notify the backend how conformant the SIMD versions
are. While the initial spec said that floating point status registers
would be not supported, this is not difficult to do and the
implementations that I wrote support this[1]. Then if a status
register is set after a calculation, the calculation can be run with
the scalar versions to determine exactly which operation(s) causes it.

[1]https://sourceware.org/ml/libc-alpha/2019-05/msg00595.html

Hi Francesco,

Nice to finally see this RFC, thanks! :)

Overall, I like the proposal. Clean, concise and complete.

I have a few comments inline, but from a high level this is looking good.

On Tue, 28 May 2019 at 20:44, Francesco Petrogalli
<Francesco.Petrogalli at arm.com> wrote:
> The directive `#pragma clang declare variant` follows the syntax of the
> `#pragma omp declare variant` directive of OpenMP.
>
> We define the new directive in the `clang` namespace instead of using
> the `omp` one of OpenMP to allow the compiler to perform
> auto-vectorization outside of an OpenMP SIMD context.
So, the only difference is that pragma "omp" includes and links OMP
stuff, while pragma "clang" doesn't, right?

What happens if I have code with "pragma clang declare variant" and
"pragma omp" elsewhere, would the clang pragma behave identically as
if it was omp?
>
> The mechanism is base on OpenMP to provide a uniform user experience
> across the two mechanism, and to maximise the number of shared
> components of the infrastructure needed in the compiler frontend to
> enable the feature.
>
> Changes in LLVM IR {#llvmIR}
> ------------------
>
> The IR is enriched with metadata that details the availability of vector
> versions of an associated scalar function. This metadata is attached to
> the call site of the scalar function.
If the metadata gets dropped by some middle-end pass, the user will be
confused why the vector function is not being called.

Do we have that problem with OMP stuff already? If so, how do we fix this?

>     // ...
>     ... = call double @sin(double) #0
>     // ...
>
>     #0 = { vector-variant = {"_ZGVcN2v_sin(__svml_sin2),
>                               _ZGVdN4v_sin(__svml_sin4),
>                               ..."} }
I'm assuming in all ABIs, the arguments and return values are
guaranteed to be the same, but vector versions. Ie. there are no
special arguments / flags / status regs that are used / changed in the
vector version that the compiler will have to "just know". If the
whole point is that this is a "variant", having specialist knowledge
for random variant ABIs won't scale.

Is that a problem or can we class those as "user-error"?
> The SVFS can add new function definitions, in the same module as the
> `Call`, to provide vector functions that are not present within the
> vector-variant metadata. For example, if a library provides a vector
> version of a function with a vectorization factor of 2, but the
> vectorizer is requesting a vectorization factor of 4, the SVFS is
> allowed to create a definition that calls the 2-lane version twice. This
> capability applies similarly for providing masked and unmasked versions
> when the request does not match what is available in the library.
Nice! Those thunks will play nicely with inlining later, sort of like unrolling.

> The `construct` set in the directive, together with the `device` set, is
> used to generate the vector mangled name to be used in the
> `vector-variant` attribute, for example `_ZGVnN2v_sin`, when targeting
> AArch64 Advanced SIMD code generation. The rule for mangling the name of
> the scalar function in the vector name are defined in the the Vector
> Function ABI specification of the target.
And I assume the user is responsible for linking the libraries that
export those signatures or they will have a linking error. Giving that
this is user definition (in the pragma), and that we really can't know
if the library will be available at link time, it's the only thing we
can do.

cheers,
--renato

On Tue, May 28, 2019 at 4:12 PM Renato Golin via llvm-dev
<llvm-dev at lists.llvm.org> wrote:
>
> Hi Francesco,
>
> Nice to finally see this RFC, thanks! :)
>
> Overall, I like the proposal. Clean, concise and complete.
>
> I have a few comments inline, but from a high level this is looking good.
>
> On Tue, 28 May 2019 at 20:44, Francesco Petrogalli
> <Francesco.Petrogalli at arm.com> wrote:
> > The directive `#pragma clang declare variant` follows the syntax of
the
> > `#pragma omp declare variant` directive of OpenMP.
> >
> > We define the new directive in the `clang` namespace instead of using
> > the `omp` one of OpenMP to allow the compiler to perform
> > auto-vectorization outside of an OpenMP SIMD context.
>
> So, the only difference is that pragma "omp" includes and links
OMP
> stuff, while pragma "clang" doesn't, right?
>
> What happens if I have code with "pragma clang declare variant"
and
> "pragma omp" elsewhere, would the clang pragma behave identically
as
> if it was omp?
>
> >
> > The mechanism is base on OpenMP to provide a uniform user experience
> > across the two mechanism, and to maximise the number of shared
> > components of the infrastructure needed in the compiler frontend to
> > enable the feature.
> >
> > Changes in LLVM IR {#llvmIR}
> > ------------------
> >
> > The IR is enriched with metadata that details the availability of
vector
> > versions of an associated scalar function. This metadata is attached
to
> > the call site of the scalar function.
>
> If the metadata gets dropped by some middle-end pass, the user will be
> confused why the vector function is not being called.
>
> Do we have that problem with OMP stuff already? If so, how do we fix this?
>
>
> >     // ...
> >     ... = call double @sin(double) #0
> >     // ...
> >
> >     #0 = { vector-variant = {"_ZGVcN2v_sin(__svml_sin2),
> >                               _ZGVdN4v_sin(__svml_sin4),
> >                               ..."} }
>
> I'm assuming in all ABIs, the arguments and return values are
> guaranteed to be the same, but vector versions. Ie. there are no
> special arguments / flags / status regs that are used / changed in the
> vector version that the compiler will have to "just know". If the
> whole point is that this is a "variant", having specialist
knowledge
> for random variant ABIs won't scale.
>
> Is that a problem or can we class those as "user-error"?
On architectures that have sticky floating point status flags, these
can be supported, and
my versions of exp and expf for PPC support them. I'd like to see the
compile know if
these work, because supporting them in the compiler is extra work
because you have
to re-run the calculation if you get a flag (and you care about which
specific operation caused
that flag).
-Shawn
>
> > The SVFS can add new function definitions, in the same module as the
> > `Call`, to provide vector functions that are not present within the
> > vector-variant metadata. For example, if a library provides a vector
> > version of a function with a vectorization factor of 2, but the
> > vectorizer is requesting a vectorization factor of 4, the SVFS is
> > allowed to create a definition that calls the 2-lane version twice.
This
> > capability applies similarly for providing masked and unmasked
versions
> > when the request does not match what is available in the library.
>
> Nice! Those thunks will play nicely with inlining later, sort of like
unrolling.
>
>
> > The `construct` set in the directive, together with the `device` set,
is
> > used to generate the vector mangled name to be used in the
> > `vector-variant` attribute, for example `_ZGVnN2v_sin`, when targeting
> > AArch64 Advanced SIMD code generation. The rule for mangling the name
of
> > the scalar function in the vector name are defined in the the Vector
> > Function ABI specification of the target.
>
> And I assume the user is responsible for linking the libraries that
> export those signatures or they will have a linking error. Giving that
> this is user definition (in the pragma), and that we really can't know
> if the library will be available at link time, it's the only thing we
> can do.
>
> cheers,
> --renato
> _______________________________________________
> LLVM Developers mailing list
> llvm-dev at lists.llvm.org
> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev

On 5/28/19 4:11 PM, Renato Golin wrote:
> Hi Francesco,
>
> Nice to finally see this RFC, thanks! :)
>
> Overall, I like the proposal. Clean, concise and complete.
>
> I have a few comments inline, but from a high level this is looking good.

+1

>
> On Tue, 28 May 2019 at 20:44, Francesco Petrogalli
> <Francesco.Petrogalli at arm.com> wrote:
>> The directive `#pragma clang declare variant` follows the syntax of the
>> `#pragma omp declare variant` directive of OpenMP.
>>
>> We define the new directive in the `clang` namespace instead of using
>> the `omp` one of OpenMP to allow the compiler to perform
>> auto-vectorization outside of an OpenMP SIMD context.
> So, the only difference is that pragma "omp" includes and links
OMP
> stuff, while pragma "clang" doesn't, right?

I'm assuming that the difference is simpler: We don't process OpenMP 
directives by default, but we will process these Clang pragmas by default.

>
> What happens if I have code with "pragma clang declare variant"
and
> "pragma omp" elsewhere, would the clang pragma behave identically
as
> if it was omp?

I think that this is an interesting question. My preference is that draw 
a distinction between 'system' directives (i.e., things provided by 
system headers, and by headers from libraries treated like system 
libraries) and user-provided directives. Then we process 
directly-conflicting directives in the following order:


Lowest priority: #pragma clang declare system variant

Medium priority: #pragma omp declare variant

Highest priority: #pragma clang declare variant


My logic is this: We should have a way for users to override variants 
provided by system headers. If users write a variant using OpenMP, it 
should override a system-provided variant. The compiler-specific (Clang) 
variant that a user provides should have the highest priority (because 
it's a Clang pragma and we're Clang). As with the general OpenMP scheme,
more-specific variants should have priority over more-general variants 
(regardless of whether they're OpenMP variants or Clang variants).

>
>> The mechanism is base on OpenMP to provide a uniform user experience
>> across the two mechanism, and to maximise the number of shared
>> components of the infrastructure needed in the compiler frontend to
>> enable the feature.
>>
>> Changes in LLVM IR {#llvmIR}
>> ------------------
>>
>> The IR is enriched with metadata that details the availability of
vector
>> versions of an associated scalar function. This metadata is attached to
>> the call site of the scalar function.
> If the metadata gets dropped by some middle-end pass, the user will be
> confused why the vector function is not being called.

Why metadata and not a call-site/function attribute?

>
> Do we have that problem with OMP stuff already? If so, how do we fix this?

I don't think that we currently use metadata like this for OpenMP in any 
relevant sense, and so we don't currently have this problem.

>
>
>>      // ...
>>      ... = call double @sin(double) #0
>>      // ...
>>
>>      #0 = { vector-variant = {"_ZGVcN2v_sin(__svml_sin2),
>>                                _ZGVdN4v_sin(__svml_sin4),
>>                                ..."} }
> I'm assuming in all ABIs, the arguments and return values are
> guaranteed to be the same, but vector versions. Ie. there are no
> special arguments / flags / status regs that are used / changed in the
> vector version that the compiler will have to "just know". If the
> whole point is that this is a "variant", having specialist
knowledge
> for random variant ABIs won't scale.
>
> Is that a problem or can we class those as "user-error"?
>
>> The SVFS can add new function definitions, in the same module as the
>> `Call`, to provide vector functions that are not present within the
>> vector-variant metadata. For example, if a library provides a vector
>> version of a function with a vectorization factor of 2, but the
>> vectorizer is requesting a vectorization factor of 4, the SVFS is
>> allowed to create a definition that calls the 2-lane version twice.
This
>> capability applies similarly for providing masked and unmasked versions
>> when the request does not match what is available in the library.
> Nice! Those thunks will play nicely with inlining later, sort of like
unrolling.
>
>
>> The `construct` set in the directive, together with the `device` set,
is
>> used to generate the vector mangled name to be used in the
>> `vector-variant` attribute, for example `_ZGVnN2v_sin`, when targeting
>> AArch64 Advanced SIMD code generation. The rule for mangling the name
of
>> the scalar function in the vector name are defined in the the Vector
>> Function ABI specification of the target.
> And I assume the user is responsible for linking the libraries that
> export those signatures or they will have a linking error.

Either user, or the driver (based on whatever compiler flags enables 
targeting the vector-math library in the first place). I'm hoping that 
the driver can get this on it's own in all common cases.

Thanks again,

Hal

>   Giving that
> this is user definition (in the pragma), and that we really can't know
> if the library will be available at link time, it's the only thing we
> can do.
>
> cheers,
> --renato
-- 
Hal Finkel
Lead, Compiler Technology and Programming Languages
Leadership Computing Facility
Argonne National Laboratory

On 5/28/19 3:31 PM, Philip Reames via cfe-dev wrote:
> I generally like the idea of having support in IR for vectorization of
> custom functions.  I have several use cases which would benefit from this.
>
> I'd suggest a couple of reframings to the IR representation though.
>
> First, this should probably be specified as metadata/attribute on a
> function declaration.  Allowing the callsite variant is fine, but it
> should primarily be a property of the called function, not of the call
> site.  Being able to specify it once per declaration is much cleaner.

I agree. We should support this both on the function declaration and on 
the call sites.

>
> Second, I really don't like the mangling use here.  We need a better
way
> to specify the properties of the function then it's mangled name.  One
> thought to explore is to directly use the Value of the function
> declaration (since this is metadata and we can do that), and then tie
> the properties to the function declaration in some way?  Sorry, I don't
> really have a specific suggestion here.

Is the problem the mangling or the fact that the mangling is 
ABI/target-specific? One option is to use LLVM's mangling scheme (the 
one we use for intrinsics) and then provide some backend infrastructure 
to translate later.


  -Hal

>
> Philip
>
> On 5/28/19 12:44 PM, Francesco Petrogalli via llvm-dev wrote:
>> Dear all,
>>
>> This RFC is a proposal to provide auto-vectorization functionality for
user provided vector functions.
>>
>> The proposal is a modification of an RFC that I have sent out a couple
of months ago, with the title `[RFC] Re-implementing -fveclib with OpenMP` (see
http://lists.llvm.org/pipermail/llvm-dev/2018-December/128426.html). The
previous RFC is to be considered abandoned.
>>
>> The original RFC was proposing to re-implement the `-fveclib` command
line option. This proposal avoids that, and limits its scope to the mechanics of
providing vector function in user code that the compiler can pick up for
auto-vectorization. This narrower scope limits the impact of changes that are
needed in both clang and LLVM.
>>
>> Please let me know what you think.
>>
>> Kind regards,
>>
>> Francesco
>>
>>
>>
================================================================================>>
>> Introduction
>> ===========>>
>> This RFC encompasses the proposal of informing the vectorizer about the
>> availability of vector functions provided by the user. The mechanism is
>> based on the use of the directive `declare variant` introduced in
OpenMP
>> 5.0 [^1].
>>
>> The mechanism proposed has the following properties:
>>
>> 1.  Decouples the compiler front-end that knows about the availability
>>      of vectorized routines, from the back-end that knows how to make
use
>>      of them.
>> 2.  Enable support for a developer's own vector libraries without
>>      requiring changes to the compiler.
>> 3.  Enables other frontends (e.g. f18) to add scalar-to-vector function
>>      mappings as relevant for their own runtime libraries, etc.
>>
>> The implemetation consists of two separate sets of changes.
>>
>> The first set is a set o changes in `llvm`, and consists of:
>>
>> 1.  [Changes in LLVM IR](#llvmIR) to provide information about the
>>      availability of user-defined vector functions via metadata
attached
>>      to an `llvm::CallInst`.
>> 2.  [An infrastructure](#infrastructure) that can be queried to retrive
>>      information about the available vector functions associated to a
>>      `llvm::CallInst`.
>> 3.  [Changes in the LoopVectorizer](#LV) to use the API to query the
>>      metadata.
>>
>> The second set consists of the changes [changes in clang](#clang) that
>> are needed too to recognize the `#pragma clang declare variant`
>> directive.
>>
>> Proposed changes
>> ===============>>
>> We propose an implementation that uses `#pragma clang declare variant`
>> to inform the backend components about the availability of vector
>> version of scalar functions found in IR. The mechanism relies in
storing
>> such information in IR metadata, and therefore makes the
>> auto-vectorization of function calls a mid-end (`opt`) process that is
>> independent on the front-end that generated such IR metadata.
>>
>> This implementation provides a generic mechanism that the users of the
>> LLVM compiler will be able to use for interfacing their own vector
>> routines for generic code.
>>
>> The implementation can also expose vectorization-specific descriptors
--
>> for example, like the `linear` and `uniform` clauses of the OpenMP
>> `declare simd` directive -- that could be used to finely tune the
>> automatic vectorization of some functions (think for example the
>> vectorization of `double sincos(double , double *, double *)`, where
>> `linear` can be used to give extra information about the memory layout
>> of the 2 pointers parameters in the vector version).
>>
>> The directive `#pragma clang declare variant` follows the syntax of the
>> `#pragma omp declare variant` directive of OpenMP.
>>
>> We define the new directive in the `clang` namespace instead of using
>> the `omp` one of OpenMP to allow the compiler to perform
>> auto-vectorization outside of an OpenMP SIMD context.
>>
>> The mechanism is base on OpenMP to provide a uniform user experience
>> across the two mechanism, and to maximise the number of shared
>> components of the infrastructure needed in the compiler frontend to
>> enable the feature.
>>
>> Changes in LLVM IR {#llvmIR}
>> ------------------
>>
>> The IR is enriched with metadata that details the availability of
vector
>> versions of an associated scalar function. This metadata is attached to
>> the call site of the scalar function.
>>
>> The metadata takes the form of an attribute containing a comma
separated
>> list of vector function mappings. Each entry has a unique name that
>> follows the Vector Function ABI[^2] and real name that is used when
>> generating calls to this vector function.
>>
>>      vfunc_name1(real_name1), vfunc_name2(real_name2)
>>
>> The Vector Function ABI name describes the signature of the vector
>> function so that properties like vectorisation factor can be queried
>> during compilation.
>>
>> The `(real name)` token is optional and assumed to match the Vector
>> Function ABI name when omitted.
>>
>> For example, the availability of a 2-lane double precision `sin`
>> function via SVML when targeting AVX on x86 is provided by the
following
>> IR.
>>
>>      // ...
>>      ... = call double @sin(double) #0
>>      // ...
>>
>>      #0 = { vector-variant = {"_ZGVcN2v_sin(__svml_sin2),
>>                                _ZGVdN4v_sin(__svml_sin4),
>>                                ..."} }
>>
>> The string `"_ZGVcN2v_sin(__svml_sin2)"` in this
vector-variant
>> attribute provides information on the shape of the vector function via
>> the string `_ZGVcN2v_sin`, mangled according to the Vector Function ABI
>> for Intel, and remaps the standard Vector Function ABI name to the
>> non-standard name `__svml_sin2`.
>>
>> This metadata is compatible with the proposal "Proposal for
function
>> vectorization and loop vectorization with function calls",[^3]
that uses
>> Vector Function ABI mangled names to inform the vectorizer about the
>> availability of vector functions. The proposal extends the original by
>> allowing the explicit mapping of the Vector Function ABI mangled name
to
>> a non-standard name, which allows the use of existing vector libraries.
>>
>> The `vector-variant` attribute needs to be attached on a per-call basis
>> to avoid conflicts when merging modules with different vector variants.
>>
>> The query infrastructure: SVFS {#infrastructure}
>> ------------------------------
>>
>> The Search Vector Function System (SVFS) is constructed from an
>> `llvm::Module` instance so it can create function definitions. The SVFS
>> exposes an API with two methods.
>>
>> ### `SVFS::isFunctionVectorizable`
>>
>> This method queries the avilability of a vectorized version of a
>> function. The signature of the method is as follows.
>>
>>      bool isFunctionVectorizable(llvm::CallInst * Call, ParTypeMap
Params);
>>
>> The method determine the availability of vector version of the function
>> invoked by the `Call` parameter by looking at the `vector-variant`
>> metadata.
>>
>> The `Params` argument is a map that associates the position of a
>> parameter in the `CallInst` to its `ParameterType` descriptor. The
>> `ParameterType` descriptor holds information about the shape of the
>> correspondend parameter in the signature of the vector function. This
>> `ParamaterType` is used to query the SVMS about the availability of
>> vector version that have `linear`, `uniform` or `align` parameters (in
>> the sense of OpenMP 4.0 and onwards).
>>
>> The method `isFunctionVectorizable`, when invoked with an empty
>> `ParTypeMap`, is equivalent to the `TargetLibraryInfo` method
>> `isFunctionVectorizable(StrinRef Name)`.
>>
>> ### `SVFS::getVectorizedFunction`
>>
>> This method returns the vector function declaration that correspond to
>> the needs of the vectorization technique that is being run.
>>
>> The signature of the function is as follows.
>>
>>      std::pair<llvm::FunctionType *, std::string>
getVectorizedFunction(
>>        llvm::CallInst * Call, unsigned VF, bool IsMasked, ParTypeSet
Params);
>>
>> The `Call` parameter is the call instance that is being vectorized, the
>> `VF` parameter represent the vectorization factor (how many lanes), the
>> `IsMasked` parameter decides whether or not the signature of the vector
>> function is required to have a mask parameter, the `Params` parameter
>> describes the shape of the vector function as in the
>> `isFunctionVectorizable` method.
>>
>> The methods uses the `vector-variant` metadata and returns the function
>> signature and the name of the function based on the input parameters.
>>
>> The SVFS can add new function definitions, in the same module as the
>> `Call`, to provide vector functions that are not present within the
>> vector-variant metadata. For example, if a library provides a vector
>> version of a function with a vectorization factor of 2, but the
>> vectorizer is requesting a vectorization factor of 4, the SVFS is
>> allowed to create a definition that calls the 2-lane version twice.
This
>> capability applies similarly for providing masked and unmasked versions
>> when the request does not match what is available in the library.
>>
>> This method is equivalent to the TLI method
>> `StringRef getVectorizedFunction(StringRef F, unsigned VF) const;`.
>>
>> Notice that to fully support OpenMP vectorization we need to think
about
>> a fuzzy matching mechanism that is able to select a candidate in the
>> calling context. However, this proposal is intended for
scalar-to-vector
>> mappings of math-like functions that are most likely to associate a
>> unique vector candidate in most contexts. Therefore, extending this
>> behavior to a generic one is an aspect of the implementation that will
>> be treated in a separate RFC about the vectorization pass.
>>
>> ### Scalable vectorization
>>
>> Both methods of the SVFS API will be extended with a boolean parameter
>> to specify whether scalable signatures are needed by the user of the
>> SVFS.
>>
>> Changes in clang {#clang}
>> ----------------
>>
>> We use clang to generate the metadata described above.
>>
>> In the compilation unit, the vector function definition or declaration
>> must be visible and associated to the scalar version via the
>> `#pragma clang declare variant` according to the rule defined by the
>> correspondent `#pragma omp declare variant` defined in OpenMP 5.0, as
in
>> the following example.
>>
>>      #pragma clang declare variant(vector_sinf) \
>>      match(construct=simd(simdlen(4),notinbranch),
device={isa("simd")})
>>      extern float sinf(float);
>>
>>      float32x4_t vector_sinf(float32x4_t x);
>>
>> The `construct` set in the directive, together with the `device` set,
is
>> used to generate the vector mangled name to be used in the
>> `vector-variant` attribute, for example `_ZGVnN2v_sin`, when targeting
>> AArch64 Advanced SIMD code generation. The rule for mangling the name
of
>> the scalar function in the vector name are defined in the the Vector
>> Function ABI specification of the target.
>>
>> The part of the vector-variant attribute that redirects the call to
>> `vector_sinf` is derived from the `variant-id` specified in the
>> `variant` clause.
>>
>> Summary
>> ======>>
>> New `clang` directive in clang
>> ------------------------------
>>
>> `#pragma omp declare variant`, same as `#pragma omp declare variant`
>> restricted to the `simd` context selector, from OpenMP 5.0+.
>>
>> Option behavior, and interaction with OpenMP
>> --------------------------------------------
>>
>> The behavior described below makes sure that
>> `#pragma cland declare variant` function vectorization and OpenMP
>> function vectorization are orthogonal.
>>
>> `-fclang-declare-variant`
>>
>> :   The `#pragma clang declare variant` directives are parsed and used
>>      to populate the `vector-variant` attribute.
>>
>> `-fopenmp[-simd]`
>>
>> :   The `#pragma omp declare variant` directives are parsed and used to
>>      populate the `vector-variant` attribute.
>>
>> `-fopenmp[-simd]`and `-fno-clang-declare-variant`
>>
>> :   The directive `#pragma omp declare variant` is used to populate the
>>      `vector-variant` attribute in IR. The directive
>>      `#pragma   clang declare variant` are ignored.
>>
>> [^1]:
<https://www.openmp.org/wp-content/uploads/OpenMP-API-Specification-5.0.pdf>
>>
>> [^2]: Vector Function ABI for x86:
>>     
<https://software.intel.com/en-us/articles/vector-simd-function-abi>.
>>      Vector Function ABI for AArch64:
>>     
https://developer.arm.com/products/software-development-tools/hpc/arm-compiler-for-hpc/vector-function-abi
>>
>> [^3]:
<http://lists.llvm.org/pipermail/cfe-dev/2016-March/047732.html>
>>
>> _______________________________________________
>> LLVM Developers mailing list
>> llvm-dev at lists.llvm.org
>> https://lists.llvm.org/cgi-bin/mailman/listinfo/llvm-dev
> _______________________________________________
> cfe-dev mailing list
> cfe-dev at lists.llvm.org
> https://lists.llvm.org/cgi-bin/mailman/listinfo/cfe-dev
-- 
Hal Finkel
Lead, Compiler Technology and Programming Languages
Leadership Computing Facility
Argonne National Laboratory