[llvm-dev] [RFC] Expose user provided vector function for auto-vectorization.
Philip Reames via llvm-dev
llvm-dev at lists.llvm.org
Tue May 28 13:31:01 PDT 2019
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>
>
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