[cfe-dev] RFC: Supporting the new PowerPC MMA instructions in Clang/LLVM

Hal Finkel via cfe-dev cfe-dev at lists.llvm.org
Mon Jun 22 16:01:37 PDT 2020

On 6/19/20 9:31 PM, Baptiste Saleil via cfe-dev wrote:
> Summary
> -------
> New Power ISA v3.1 [0] introduces instructions to accelerate matrix
> multiplication. We want to expose these instructions through a list of
> target-dependent builtins and new Clang types in the form of a language
> extension. This RFC gives more details on the requirements for these
> types and explains how we (IBM) are implementing them in Clang.
> We present the frontend implementation as an RFC because we need to add
> target-specific checks in Sema and want to get feedback on our 
> implementation
> of these checks. The backend implementation does not impact the other 
> targets
> so it is not part of this RFC. Comments and questions are welcome.
> Introduction
> ------------
> The new instructions manipulate matrices that the CPU represents by 
> new 512-bit
> registers called `accumulators`. Copying matrices, modifying values and
> extracting values of matrices may cause the CPU to copy values from/to the
> matrix multiplication unit. To avoid degrading performance, we thus 
> want to
> minimize the number of times these operations are used. So the user 
> will be able
> to modify and extract values of the matrices and perform computations 
> with them
> by using the dedicated builtins only. The instructions are designed to 
> be used in
> computational kernels and we want to enforce that specific workflow.
> Because of this restriction, we cannot rely on the target-independent 
> matrix
> types [1].

If this is part of the documented system ABI, and what will be supported 
by GCC, then we should support it too.

That having been said, I'm not convinced that this is a good idea, and 
supporting the target-independent matrix types would be better. I 
understand that the copying will be expensive, and is something that 
should be avoided, but this is true to some extent for everything: there 
are some usages that compile to machine code efficiently and some that 
don't. We generally, however, favor the ability to create abstractions 
that *can* be compiled efficiently as part of expected use cases, even 
if we cannot guarantee that all uses will produce efficient code. In his 
case, you're prohibiting the creation of abstractions (by semantically 
restricting to local variables) because you fear that not all uses will 
compile to efficient code. Are there some other structural reasons why 
supporting these are regular values would be problematic?

> We need to add a new target-dependent type and restrict its use.
> We give more details on these restrictions below. To be able to manipulate
> these matrices, we want to add the `__vector_quad` type to Clang. This 
> type
> would be a PowerPC-specific builtin type mapped to the new 512-bit 
> registers.



> Similarly, some of these instructions take 256-bit values that must be 
> stored
> in two consecutive VSX registers. To represent these values and 
> minimize the
> number of copies between VSX registers, we also want to add the 
> PowerPC-specific
> builtin type `__vector_pair` that would be mapped to consecutive VSX 
> registers.
> Value initialization
> --------------------
> The only way to initialize a `__vector_pair` is by calling a builtin 
> taking two
> 128-bit vectors and assembling them to form a 256-bit pair. A similar 
> builtin
> exists to assemble four 128-bit vectors to form a 512-bit `__vector_quad`:
> vector unsigned char v1 = ...;
> vector unsigned char v2 = ...;
> vector unsigned char v3 = ...;
> vector unsigned char v4 = ...;
> __vector_pair vp;
> __vector_quad vq;
> __builtin_mma_assemble_pair(&vp, v1, v2);
> __builtin_mma_assemble_acc(&vq, v1, v2, v3, v4);
> The other way to initialize a `__vector_quad` is to call a builtin 
> mapped to an
> instruction generating a new value of this type:
> __vector_quad vq1;
> __builtin_mma_xxsetaccz(&vq1); // zero-initializes vq1
> __vector_quad vq2;
> __builtin_mma_xvi4ger8(&vq2, v1, v2); // new value generated in vq2
> Both `__vector_pair` and `__vector_quad` can also be loaded from 
> pointers that
> can potentially be casted from void or char pointers.
> Value extraction
> ----------------
> The only way to extract values from a matrix is to call the builtins
> disassembling `__vector_pair` and `__vector_quad` values back into two
> and four 128-bit vectors respectively:
> vector unsigned char* vpr = ...;
> vector unsigned char* vqr = ...;
> __builtin_mma_disassemble_pair(vpr, &vp);
> __builtin_mma_disassemble_acc(vqr, &vq);
> Once the values are disassembled to vectors, the user can extract 
> values as
> usual, for example using the subscript operator on the vector unsigned 
> char
> values. So the typical workflow to efficiently use these instructions in a
> kernel is to first initialize the matrices, then perform computations 
> and finally
> disassemble them to extract the result of the computations. These 
> three steps
> should be done using the provided builtins.
> Semantics
> ---------
> To enforce using values of these types in kernels, thus to avoid 
> copies from/to
> the matrix multiplication unit, we want to prevent as many implicit copies
> as possible. That means that it should only be possible to declare 
> values of
> these types as local variables. We want to prevent any other way to 
> declare and
> use non-pointer variables of these types (global variable, function 
> parameter,
> function return, etc...).
> The only situations in which these types and values of these types can be
> used are:
>   * Local variable declaration
>   * Assignment operator
>   * Builtin call parameter
>   * Memory allocation
>   * Typedef & alias
> Implementation
> --------------
> We have implemented the support of these types, builtins and 
> intrinsics in both
> Clang's frontend and the LLVM PowerPC backend. We will post the backend
> implementation later. We implemented and tested this support 
> out-of-tree in
> conjunction with the GCC team to ensure a common API and ensure source
> compatibility. For this RFC, we have 5 patches for the frontend:
>   * Add options to control MMA support on PowerPC targets [2].
>   * Define the two new types as Clang target-dependent builtin types.
>     As the other targets, we decided to define these types in a separate
>     `PPCtypes.def` file to improve extensibility in case we need to 
> add other
>     PowerPC-specific types in the future [3].
>   * Add the builtin definitions. These builtins use the two new types,
>     so they use custom type descriptors. To avoid pervasive changes,
>     we use custom decoding of these descriptors [4].
>   * Add the Sema checks to restrict the use of the two types.
>     We prevent the use of non-pointer values of these types in any 
> declaration
>     that is not a local variable declaration. We also prevent them to
>     be passed as function arguments and to be returned from functions [5].
>   * Implement the minimal required changes to LLVM to support the 
> builtins.
>     In this patch, we enable the use of v256i1 for intrinsic arguments and
>     define all the MMA intrinsics the builtins are mapped to [6].
> The backend implementation should not impact other targets. We do not 
> plan to
> add any type to LLVM. `__vector_pair` and `__vector_quad` are generated as
> `v256i1` and `v512i1` respectively (both are currently unused in the 
> PowerPC
> backend). VSX pair registers will be allocated to the `v256i1` type 
> and the
> new accumulator registers will be allocated to the `v512i1` type.
> [0] Power ISA v3.1, 
> https://ibm.ent.box.com/s/hhjfw0x0lrbtyzmiaffnbxh2fuo0fog0 
> <https://ibm.ent.box.com/s/hhjfw0x0lrbtyzmiaffnbxh2fuo0fog0>
> [1] https://clang.llvm.org/docs/MatrixTypes.html 
> <https://clang.llvm.org/docs/MatrixTypes.html>
> [2] https://reviews.llvm.org/D81442 <https://reviews.llvm.org/D81442>
> [3] https://reviews.llvm.org/D81508 <https://reviews.llvm.org/D81508>
> [4] https://reviews.llvm.org/D81748 <https://reviews.llvm.org/D81748>
> [5] https://reviews.llvm.org/D82035 <https://reviews.llvm.org/D82035>
> [6] https://reviews.llvm.org/D81744 <https://reviews.llvm.org/D81744>
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Hal Finkel
Lead, Compiler Technology and Programming Languages
Leadership Computing Facility
Argonne National Laboratory

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