Commit Graph

29 Commits

Author SHA1 Message Date
Florian Hahn f13a59bcff [Matrix] Use TileInfo to create tiled loop nest for matrix multiply.
This patch uses the TileInfo introduced in D77550 to generate a loop
nest for tiled matrix multiplication, instead of generating the
unrolled code for the whole multiplication. This makes code-generation
more scalable for larger matrixes.

Initially loops are only used if both the number of rows and columns are
divisible by the tile size. Other cases will be added as follow-up.

Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor, LuoYuanke, nicolasvasilache

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D81308
2020-07-20 21:11:53 +01:00
Florian Hahn dc1087d408 [Matrix] Add minimal lowering pass that only requires TTI.
This patch adds a new variant of the matrix lowering pass that only does
a minimal lowering and only depends on TTI. The main purpose of this pass
is to have a pass with minimal dependencies to run as part of the backend
pipeline.

At the moment, the only difference to the regular lowering pass is that it
does not support remarks. But in subsequent patches add support for tiling
to the lowering pass which will require more analysis, which we do not want
to run in the backend, as the lowering should happen in the middle-end in
practice and running it in the backend is mostly for convenience when
running llc.

Reviewers: anemet, Gerolf, efriedma, hfinkel

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D76867
2020-07-20 11:16:11 +01:00
Sjoerd Meijer 2b3c505d0f [Matrix] Intrinsic descriptions
This changes the matrix load/store intrinsic definitions to load/store from/to
a pointer, and not from/to a pointer to a vector, as discussed in D83477.

This also includes the recommit of "[Matrix] Tighten LangRef definitions and
Verifier checks" which adds improved language reference descriptions of the
matrix intrinsics and verifier checks.

Differential Revision: https://reviews.llvm.org/D83785
2020-07-14 19:58:16 +01:00
Dmitry Polukhin 9e7fddbd36 [yaml][clang-tidy] Fix multiline YAML serialization
Summary:
New line duplication logic introduced in https://reviews.llvm.org/D63482
has two issues: (1) there is no logic that removes duplicate newlines
when clang-apply-replacment reads YAML and (2) in general such logic
should be applied to all strings and should happen on string
serialization level instead in YAML parser.

This diff changes multiline strings quotation from single quote `'` to
double `"`. It solves problems with internal newlines because now they are
escaped. Also double quotation solves the problem with leading whitespace after
newline. In case of single quotation YAML parsers should remove leading
whitespace according to specification. In case of double quotation these
leading are internal space and they are preserved. There is no way to
instruct YAML parsers to preserve leading whitespaces after newline so
double quotation is the only viable option that solves all problems at
once.

Test Plan: check-all

Reviewers: gribozavr, mgehre, yvvan

Subscribers: xazax.hun, hiraditya, cfe-commits, llvm-commits

Tags: #clang-tools-extra, #clang, #llvm

Differential Revision: https://reviews.llvm.org/D80301
2020-07-09 02:41:58 -07:00
Florian Hahn 1669fddc9f [Matrix] Use alignment info when lowering loads/stores.
This patch updates LowerMatrixIntrinsics to preserve the alignment
specified at the original load/stores and the align attribute for the
pointer argument of the column.major.load/store intrinsics.

We can always use the specified alignment for the load of the first
column. For subsequent columns, the alignment may need to be reduced.

For ConstantInt strides, compute the offset for the start of the column in
bytes and use commonAlignment to get the largest valid alignment.

For non-ConstantInt strides, we need to take the common alignment of the
initial alignment and the element size in bytes.

Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor, LuoYuanke, rjmccall

Reviewed By: rjmccall

Differential Revision: https://reviews.llvm.org/D81960
2020-06-18 13:19:31 +01:00
Florian Hahn d88acd8f7d [Matrix] Preserve volatile when loading loads/stores.
Currently the matrix lowering turns volatile loads/stores into
non-volatile ones. This patch updates the lowering to preserve the
volatile bit.

Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor, LuoYuanke, nicolasvasilache

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D81498
2020-06-18 12:14:19 +01:00
Florian Hahn 9ce89b3b64 [Matrix] Add volatile load/store tests (NFC). 2020-06-18 09:57:13 +01:00
Florian Hahn 6d18c2067e [Matrix] Update load/store intrinsics.
This patch adjust the load/store matrix intrinsics, formerly known as
llvm.matrix.columnwise.load/store, to improve the naming and allow
passing of extra information (volatile).

The patch performs the following changes:
 * Rename columnwise.load/store to column.major.load/store. This is more
   expressive and also more in line with the naming in Clang.
 * Changes the stride arguments from i32 to i64. The stride can be
   larger than i32 and this makes things more uniform with the way
   things are handled in Clang.
 * A new boolean argument is added to indicate whether the load/store
   is volatile. The lowering respects that when emitting vector
   load/store instructions
 * MatrixBuilder is updated to require both Alignment and IsVolatile
   arguments, which are passed through to the generated intrinsic. The
   alignment is set using the `align` attribute.

The changes are grouped together in a single patch, to have a single
commit that breaks the compatibility. We probably should be fine with
updating the intrinsics, as we did not yet officially support them in
the last stable release. If there are any concerns, we can add
auto-upgrade rules for the columnwise intrinsics though.

Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor, LuoYuanke, nicolasvasilache, rjmccall, ftynse

Reviewed By: anemet, nicolasvasilache

Differential Revision: https://reviews.llvm.org/D81472
2020-06-18 09:44:52 +01:00
Florian Hahn 08f62ff8ef [Matrix] Add align info to some more loads/stores (NFC).
Some tests were missing alignment info. Subsequent changes properly
preserve the set alignment. Set it properly beforehand, to avoid
unnecessary test changes.
2020-06-16 20:42:59 +01:00
Florian Hahn e02c964969 [Matrix] Specify missing alignment in tests (NFC).
Some tests were missing alignment info. Subsequent changes properly
preserve the set alignment. Set it properly beforehand, to avoid
unnecessary test changes.

It also updates cases where an alignment of 16 was specified, instead of
the vector element type alignment.
2020-06-16 15:37:35 +01:00
Florian Hahn 1d33c09f22 [IR] Add nocapture & nosync to matrix intrinsics.
As suggested in D81472, the load/store intrinsics' pointer arguments can
be marked as nocapture and all matrix intrinsics as nosync.

This also re-flows the intrinsic definitions, to make them a little more
concise.
2020-06-15 22:07:40 +01:00
Florian Hahn 3631239b26 [Matrix] Update check lines for strided intrinsics (NFC).
This re-generates some check lines, after the naming of values got
improved, to reduce the size of diffs in follow-on patches.
2020-06-09 15:51:00 +01:00
aartbik f719e7d9e7 [llvm] [MatrixIntrinsics] Add row-major support for llvm.matrix.transpose
Summary:
Only column-major was supported so far. This adds row-major support as well.
Note that we probably also want very efficient SIMD implementations for the
various target platforms.

Bug:
https://bugs.llvm.org/show_bug.cgi?id=46085

Reviewers: nicolasvasilache, reidtatge, bkramer, fhahn, ftynse, andydavis1, craig.topper, dcaballe, mehdi_amini, anemet

Reviewed By: fhahn

Subscribers: hiraditya, llvm-commits

Tags: #llvm

Differential Revision: https://reviews.llvm.org/D80673
2020-05-28 12:13:32 -07:00
Florian Hahn 39f2d9aa81 [Matrix] Add option to use row-major matrix layout as default.
This patch adds a -matrix-default-layout option which can be used to
set the default matrix layout to row-major or column-major (default).

The initial patch updates codegen for loads, stores, binary operators
and matrix multiply.

Reviewers: anemet, Gerolf, andrew.w.kaylor, LuoYuanke

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D76325
2020-04-06 10:00:56 +01:00
Florian Hahn d1fed7081d [Matrix] Add initial tiling for load/multiply/store chains.
This patch adds initial fusion for load/multiply/store chains of matrix
operations.

The patch contains roughly two parts:

1. Code generation for a fused load/multiply/store chain (LowerMatrixMultiplyFused).
First, we ensure that both loads of the multiply operands do not alias the store.
If they do, we create new non-aliasing copies of the operands. Note that this
may introduce new basic block. Finally we process TileSize x TileSize blocks.
That is: load tiles from the input operands, multiply and store them.

2. Identify fusion candidates & matrix instructions.
As a first step, collect all instructions with shape info and fusion candidates
(currently @llvm.matrix.multiply calls). Next, try to fuse candidates and
collect instructions eliminated by fusion. Finally iterate over all matrix
instructions, skip the ones eliminated by fusion and lower the rest as usual.

Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor, LuoYuanke

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D75566
2020-04-06 09:28:15 +01:00
Florian Hahn e20cac3650 [Matrix] Add new test case with getelementptr constant exprs.
The new test mostly ensures we keep doing the right thing for constant
expressions while lowering matrix instructions.
2020-04-01 09:32:13 +01:00
Florian Hahn bc6c8c4bbb [Matrix] Add remark propagation along the inlined-at chain.
This patch adds support for propagating matrix expressions along the
inlined-at chain and emitting remarks at the traversed function scopes.

To motivate this new behavior, consider the example below. Without the
remark 'up-leveling', we would only get remarks in load.h and store.h,
but we cannot generate a remark describing the full expression in
toplevel.cpp, which is the place where the user has the best chance of
spotting/fixing potential problems.

With this patch, we generate a remark for the load in load.h, one for
the store in store.h and one for the complete expression in
toplevel.cpp. For a bigger example, please see remarks-inlining.ll.

    load.h:
    template <typename Ty, unsigned R, unsigned C> Matrix<Ty, R, C> load(Ty *Ptr) {
      Matrix<Ty, R, C> Result;
      Result.value = *reinterpret_cast <typename Matrix<Ty, R, C>::matrix_t *>(Ptr);
      return Result;
    }

    store.h:
    template <typename Ty, unsigned R, unsigned C> void store(Matrix<Ty, R, C> M1, Ty *Ptr) {
       *reinterpret_cast<typename decltype(M1)::matrix_t *>(Ptr) = M1.value;
    }

    toplevel.cpp
    void test(double *A, double *B, double *C) {
      store(add(load<double, 3, 5>(A), load<double, 3, 5>(B)), C);
    }

For a given function, we traverse the inlined-at chain for each
matrix instruction (= instructions with shape information). We collect
the matrix instructions in each DISubprogram we visit. This produces a
mapping of DISubprogram -> (List of matrix instructions visible in the
subpogram). We then generate remarks using the list of instructions for
each subprogram in the inlined-at chain. Note that the list of instructions
for a subprogram includes the instructions from its own subprograms
recursively. For example using the example above, for the subprogram
'test' this includes inline functions 'load' and 'store'. This allows
surfacing the remarks at a level useful to users.

Please note that the current approach may create a lot of extra remarks.
Additional heuristics to cut-off the traversal can be implemented in the
future. For example, it might make sense to stop 'up-leveling' once all
matrix instructions are at the same debug location.

Reviewers: anemet, Gerolf, thegameg, hfinkel, andrew.w.kaylor, LuoYuanke

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D73600
2020-03-11 17:40:08 +00:00
Florian Hahn 8c681f5e47 [Matrix] Mark matrix memory intrinsics as argmemonly/write|read mem.
matrix.columnwise.load and matrix.columnwise.store only access memory
through the argument pointers. Also matrix.columnwise.store only writes
memory.
2020-02-04 12:32:45 +00:00
Florian Hahn 5d0ffbeb4d [Matrix] Mark expressions shared between multiple remarks.
This patch adds support for explicitly highlighting sub-expressions
shared by multiple leaf nodes. For example consider the following
code

  %shared.load = tail call <8 x double> @llvm.matrix.columnwise.load.v8f64.p0f64(double* %arg1, i32 %stride, i32 2, i32 4), !dbg !10, !noalias !10
  %trans = tail call <8 x double> @llvm.matrix.transpose.v8f64(<8 x double> %shared.load, i32 2, i32 4), !dbg !10
  tail call void @llvm.matrix.columnwise.store.v8f64.p0f64(<8 x double> %trans, double* %arg3, i32 10, i32 4, i32 2), !dbg !10
  %load.2 = tail call <30 x double> @llvm.matrix.columnwise.load.v30f64.p0f64(double* %arg3, i32 %stride, i32 2, i32 15), !dbg !10, !noalias !10
  %mult = tail call <60 x double> @llvm.matrix.multiply.v60f64.v8f64.v30f64(<8 x double> %trans, <30 x double> %load.2, i32 4, i32 2, i32 15), !dbg !11
  tail call void @llvm.matrix.columnwise.store.v60f64.p0f64(<60 x double> %mult, double* %arg2, i32 10, i32 4, i32 15), !dbg !11

We have two leaf nodes (the 2 stores) and the first store stores %trans
which is also used by the matrix multiply %mult. We generate separate
remarks for each leaf (stores). To denote that parts are shared, the
shared expressions are marked as shared (), with a reference to the
other remark that shares it. The operation summary also denotes the
shared operations separately.

Reviewers: anemet, Gerolf, thegameg, hfinkel, andrew.w.kaylor, LuoYuanke

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D72526
2020-01-28 09:27:55 -08:00
Florian Hahn 6f07f304a2 [Matrix] Mark remarks test as AArch64 specific. 2020-01-27 18:00:43 -08:00
Florian Hahn 62e228f8fd [Matrix] Add info about number of operations to remarks.
This patch updates the remark to also include a summary of the number of
vector operations generated for each matrix expression.

Reviewers: anemet, Gerolf, thegameg, hfinkel, andrew.w.kaylor, LuoYuanke

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D72480
2020-01-27 17:43:39 -08:00
Florian Hahn 949294f396 [Matrix] Add optimization remarks for matrix expression.
Generate remarks for matrix operations in a function. To generate remarks
for matrix expressions, the following approach is used:
1. Collect leafs of matrix expressions (done in
   RemarkGenerator::getExpressionLeafs).  Leafs are lowered matrix
   instructions without other matrix users (like stores).

2. For each leaf, create a remark containing a linearizied version of the
   matrix expression.

The following improvements will be submitted as follow-ups:
* Summarize number of vector instructions generated for each expression.
* Account for shared sub-expressions.
* Propagate matrix remarks up the inlining chain.

The information provided by the matrix remarks helps users to spot cases
where matrix expression got split up, e.g. due to inlining not
happening. The remarks allow users to address those issues, ensuring
best performance.

Reviewers: anemet, Gerolf, thegameg, hfinkel, andrew.w.kaylor, LuoYuanke

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D72453
2020-01-27 16:39:29 -08:00
Florian Hahn ccf24225e3 [Matrix] Update shape propagation to iterate until done.
This patch updates the shape propagation to iterate until no new shape
information is discovered.

As initial seed for the forward propagation, we use the matrix intrinsic
instructions. Both propagateShapeForward and propagateShapeBackward
return new work lists, with the instructions to be used for the next
iteration. When propagating forward, we record all instructions we added
new shape information for. When propagating backward, we record all
users of instructions we added new shape information for.

Reviewers: anemet, Gerolf, reames, hfinkel, andrew.w.kaylor

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D70901
2020-01-09 10:52:52 +00:00
Florian Hahn 7adf6644f5 [Matrix] Propagate and use shape information for loads.
This patch extends to shape propagation to also include load
instructions and implements shape aware lowering for vector loads.

Reviewers: anemet, Gerolf, reames, hfinkel, andrew.w.kaylor

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D70900
2020-01-09 10:21:20 +00:00
Florian Hahn 459ad8e97e [Matrix] Implement back-propagation of shape information.
This patch extends the shape propagation for matrix operations to also
propagate the shape of instructions to their operands.

Reviewers: anemet, Gerolf, reames, hfinkel, andrew.w.kaylor

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D70899
2020-01-09 09:48:07 +00:00
Florian Hahn dc2c9b0fcf [Matrix] Propagate and use shape info for binary operators.
This patch extends the current shape propagation and shape aware
lowering to also support binary operators. Those operators are uniform
with respect to their shape (shape of the input operands is the same as
the shape of their result).

Reviewers: anemet, Gerolf, reames, hfinkel, andrew.w.kaylor

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D70898
2019-12-27 15:50:47 +00:00
Florian Hahn 8d6f59b78a [Matrix] Use fmuladd for matrix.multiply if allowed.
If the matrix.multiply calls have the contract fast math flag, we can
use fmuladd. This als adds a command line option to force fmuladd
generation. We can retire this option once there is a clang-level
option.

Reviewers: anemet, Gerolf, hfinkel, andrew.w.kaylor

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D70951
2019-12-23 14:49:14 +01:00
Florian Hahn 109e4e3851 [Matrix] Add forward shape propagation and first shape aware lowerings.
This patch adds infrastructure for forward shape propagation to
LowerMatrixIntrinsics. It also updates the pass to make use of
the shape information to break up larger vector operations and to
eliminate unnecessary conversion operations between columnwise matrixes
and flattened vectors: if shape information is available for an
instruction, lower the operation to a set of instructions operating on
columns. For example, a store of a matrix is broken down into separate
stores for each column. For users that do not have shape
information (e.g. because they do not yet support shape information
aware lowering), we pack the result columns into a flat vector and
update those users.

It also adds shape aware lowering for the first non-intrinsic
instruction: vector stores.

Example:

For
  %c  = call <4 x double> @llvm.matrix.transpose(<4 x double> %a, i32 2, i32 2)
  store <4 x double> %c, <4 x double>* %Ptr

We generate the code below without shape propagation. Note %9 which
combines the columns of the transposed matrix into a flat vector.

  %split = shufflevector <4 x double> %a, <4 x double> undef, <2 x i32> <i32 0, i32 1>
  %split1 = shufflevector <4 x double> %a, <4 x double> undef, <2 x i32> <i32 2, i32 3>
  %1 = extractelement <2 x double> %split, i64 0
  %2 = insertelement <2 x double> undef, double %1, i64 0
  %3 = extractelement <2 x double> %split1, i64 0
  %4 = insertelement <2 x double> %2, double %3, i64 1
  %5 = extractelement <2 x double> %split, i64 1
  %6 = insertelement <2 x double> undef, double %5, i64 0
  %7 = extractelement <2 x double> %split1, i64 1
  %8 = insertelement <2 x double> %6, double %7, i64 1
  %9 = shufflevector <2 x double> %4, <2 x double> %8, <4 x i32> <i32 0, i32 1, i32 2, i32 3>
  store <4 x double> %9, <4 x double>* %Ptr

With this patch, we propagate the 2x2 shape information from the
transpose to the store and we generate the code below. Note that we
store the columns directly and do not need an extra shuffle.

  %9 = bitcast <4 x double>* %Ptr to double*
  %10 = bitcast double* %9 to <2 x double>*
  store <2 x double> %4, <2 x double>* %10, align 8
  %11 = getelementptr double, double* %9, i32 2
  %12 = bitcast double* %11 to <2 x double>*
  store <2 x double> %8, <2 x double>* %12, align 8

Reviewers: anemet, Gerolf, reames, hfinkel, andrew.w.kaylor

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D70897
2019-12-23 13:51:56 +01:00
Florian Hahn 526244b187 [Matrix] Add first set of matrix intrinsics and initial lowering pass.
This is the first patch adding an initial set of matrix intrinsics and a
corresponding lowering pass. This has been discussed on llvm-dev:
http://lists.llvm.org/pipermail/llvm-dev/2019-October/136240.html

The first patch introduces four new intrinsics (transpose, multiply,
columnwise load and store) and a LowerMatrixIntrinsics pass, that
lowers those intrinsics to vector operations.

Matrixes are embedded in a 'flat' vector (e.g. a 4 x 4 float matrix
embedded in a <16 x float> vector) and the intrinsics take the dimension
information as parameters. Those parameters need to be ConstantInt.
For the memory layout, we initially assume column-major, but in the RFC
we also described how to extend the intrinsics to support row-major as
well.

For the initial lowering, we split the input of the intrinsics into a
set of column vectors, transform those column vectors and concatenate
the result columns to a flat result vector.

This allows us to lower the intrinsics without any shape propagation, as
mentioned in the RFC. In follow-up patches, we plan to submit the
following improvements:
 * Shape propagation to eliminate the embedding/splitting for each
   intrinsic.
 * Fused & tiled lowering of multiply and other operations.
 * Optimization remarks highlighting matrix expressions and costs.
 * Generate loops for operations on large matrixes.
 * More general block processing for operation on large vectors,
   exploiting shape information.

We would like to add dedicated transpose, columnwise load and store
intrinsics, even though they are not strictly necessary. For example, we
could instead emit a large shufflevector instruction instead of the
transpose. But we expect that to
  (1) become unwieldy for larger matrixes (even for 16x16 matrixes,
      the resulting shufflevector masks would be huge),
  (2) risk instcombine making small changes, causing us to fail to
      detect the transpose, preventing better lowerings

For the load/store, we are additionally planning on exploiting the
intrinsics for better alias analysis.

Reviewers: anemet, Gerolf, reames, hfinkel, andrew.w.kaylor, efriedma, rengolin

Reviewed By: anemet

Differential Revision: https://reviews.llvm.org/D70456
2019-12-12 15:42:18 +00:00