Commit Graph

19 Commits (cd44a35177cc9ae4edd4e3e32a8a22fab7e3a56f)

Author SHA1 Message Date
Sean Silva 83b5b5456d Bump llvm-project to da289a174fc6617c7be37be2947480510fd4f02a
- Build adjustments for `.cpp.inc` dialect files.
- Renaming of `memref.dim` to `tensor.dim` for tensor case.

Minor changes:
- Renaming of `mlir::linalg::ReassociationIndices` to
  `mlir::ReassociationIndices`.
- Adjust command line option parsing in npcomp-run-mlir.
2021-07-07 13:57:29 -07:00
Stella Laurenzo a3f4db9fe8 Bump llvm-project to c8c07b76b2cf2ada8e7ec132f7f57b97d76743cf.
* Several NFC changes to signatures/includes.
2020-10-29 15:25:55 -07:00
Stella Laurenzo af4edb63ae Start reworking towards a shared library build.
* Need to have a dag of shared library deps in order to interop across python extensions (as presented in ODM).
* Introduced add_npcomp_library and friends to mirror the MLIR setup.
* Adds a libNPCOMP.so shared library.
* Redirects tools and extensions to link against libNPCOMP.so (instead of static libs).
* Moves all libraries to lib/, all binaries to bin/ and all python extensions to python/. The invariant is that the rpaths are setup to have a one level directory structure.
* Reworks the _torch_mlir extension to build like the others (still need to come up with a consolidated rule to do this instead of open coded).
* Includes an upstream version bump to pick up needed changes.

Sizes with dynamic linking (stripped, release, asserts enabled):
  libNPCOMP.so: 43M (includes much of the underlying LLVM codegen deps)
  libMLIR.so: 31M
  _npcomp.so: 1.6M (python extension)
  _torch_mlir.so: 670K (python extension)
  npcomp-capi-ir-test: 6.3K
  npcomp-opt: 351K
  npcomp-run-mlir: 461K
  mnist-playground: 530K

Still more can be done to normalize and optimize but this gets us structurally to the starting point.
2020-10-09 16:02:58 -07:00
Sean Silva 03846ed8e7 Rename a couple CMake targets.
NPCOMPFoo to NPCOMPFooDialect for consistency with others.
2020-10-07 10:29:48 -07:00
Sean Silva 5017430dc7 [RefBackend] Split out RefBackend (refback) dialect from TCP.
This is the first in a patch series that is refactoring the
constellation of things variously called or associated with "E2E",
"RefE2E", "npcomprt", and "TCP" into a more cleanly layered result.

Concretely, this first patch fixes the fact that TCP was basically
acting like a dumping ground needed by the reference backend. This
splits it out, which is fairly mechanical, but touches a lot of lines of
code (basically replacing `tcp` with `refback` and `TCP` with
`RefBackend).

Now, the RefBackend dialect is that dumping ground, which
is slighly better, as it starts allowing TCP to become a nice clean
middle layer that is not related per se to the reference backend.

The previous name RefE2E or "reference e2e flow" was super confusing.
Now that we are seeing more clearly where the "backend" distinction
lies, the [RefBackend] commit tag is born :)
2020-10-07 10:29:48 -07:00
Sean Silva 6ea37cfed6 Bump llvm-project to 9ed1e5873c19eb817fb9e36d0262c7effee5d35e
Date:   Fri Sep 18 13:55:52 2020 -0700

- Update to linalg syntax
- New generated builders are better. Custom builder for
tcp.shaped_results is now redundant.
2020-09-28 09:34:44 -07:00
Sean Silva 75f57b461e
Totally rework RefE2E tensor to memref flow. (#42)
This now gets the overall "RefE2E" compilation stack to a point that I'm
fairly happy with. We simplify it by mostly embracing the "descriptor"
view of the world.

The overall flow is best understood by reading through the
createE2ELoweringPipeline function in lib/E2E/E2E.cpp
That function creates a pass pipeline that lowers from "TCF" (which is
~numpy level of abstraction) down to LLVM IR.

A brief high-level summary of what happens there:

1. TCF to TCP conversion. This involves reifying error handling in the
form of shape constraints. See test/Conversion/TCFToTCP/basic.mlir

2. Lowering shape constraints. This converts shape constraints into
eager error-handling code. See test/E2E/lower-shape-constraints.mlir
This pass will soon go upstream.
Because this lowers to std.assert, some later passes like
LowerToNpcomprtABI and LowerToLLVM are updated to properly plumb this
through e2e.
See test/npcomp-run-mlir/invalid-broadcast.mlir for an execution test
that properly aborts in case of an error.

3. Lowering tensors to memrefs. This is done via a series of passes
rather than an single mega conversion. Unlike the previous code that
mixed in the npcomprt ABI stuff here, it's now a very clean "pure
memref" conversion.
See test/E2E/lower-*-to-memref.mlir and
lib/E2E/TensorToMemref/
Most of the changes are concentrated here.

4. As part of the above, we use the upstream ConvertShapeToStandard for
lowering shapes.

5. We lower linalg to loops and lower loops to CFG using upstream
passes.

6. Rewrite the "ABI" boundaries of the program to npcomprt data
structures (LowerToNpcomprtABI). This mainly affects ABI boundaries and
how global tensor constants are represented. One of the major
improvements in this commit is that now it's a very clean rewrite that
just replaces memrefs on ABI boundaries with !npcomprt.tensor (before
there was a get_extent function that is not needed).
See test/E2E/lower-to-npcomprt-abi.mlir

7. Lower to LLVM with upstream mlir patterns + some patterns for the
npcomprt lowerings.

One aspect here that is still a remnant of a non-descriptor-based tensor
to memref flow is the BypassShapes + LowerShapedResultsToMemref.
BypassShapes wraps the "tensor compute" ops in a tcp.shaped_results
(basically a "tie_shape" kind of op), and then
LowerShapedResultsToMemref uses those annotations to allocate output
buffers while lowering the "tensor compute ops". Note that there are
very few "tensor compute" ops currently supported (tcp.add +
tcp.broadcast_to), so we just hardcode them in both passes.
Realistically, I expect this to go away as we fully embrace the
descriptor-based approach for simplicity, so don't look too deep into
it.
2020-09-16 17:31:40 -07:00
Marius Brehler d62f8227c2
Bump LLVM to @7d1ed69 and fix namespace handling changed upstream.
* Bump LLVM to llvm/llvm-project@7d1ed69
* Bump MLIR-HLO to tensorflow/mlir-hlo@1880f87
* Adopt to MLIR's changed namespace handling
2020-09-16 15:52:15 -07:00
Stella Laurenzo 97d83f786a Bump submodule versions.
* llvm-project: b5924a8e27536d19dd5c4d302db29fb6163d5faa
* mhlo: 848ca244d20f045b7921da55a98a04d95ef94f0e
* Multiple breakages that need to be fixed.

Fixes:
* Refactor dialect registration
* Remove all kindof methods (Casting functionality has been added upstream and is implicitly
available, see https://llvm.discourse.group/t/removing-kinds-from-attributes-and-types/1547.)
* Update dialect registration to comply with https://reviews.llvm.org/D85495.
* Remove type kinds and update some changed dialect signatures.
* Upgrade ATen dialect to match upstream needs.
  * Move dialect registration to tablegen.
  * Register the ListType in tablegen.
  * Change dialect initialization signature.
* Use TypeSwitch in MlirIr location printer.
* Remove global registry depends from npcomp-opt.
* Change LowerToLLVM to pass an MLIRContext vs an LLVMDialect for type creation.
* Remove dep on MLIREDSCInterface that is removed upstream.
* Thread through the DialectRegistry for opt and python-like tools.
* Modernize pass registration (This was forced because the GEN_PASS_REGISTRATION code now generates inline functions vs literal pass registration statements)

Co-authored-by: Marius Brehler <marius.brehler@iml.fraunhofer.de>
2020-09-08 13:26:42 -07:00
Stella Laurenzo 9d5d802cc8 Fix compilation issues due to llvm-project version bump.
* Redundant infer type implementations removed.
* Update to the linalg GenericOp build calls.
2020-08-01 15:23:57 -07:00
Sean Silva e228aa4b11 npcomprt: add support for constants
- create tcp.global + tcp.get_global_memref
- create npcomprt.global + npcomprt.get_global
- LLVM lowering for new npcomprt ops
- Runtime:
 - GlobalDescriptor struct emitted by LLVM lowering
 - implement __npcomp_compiler_rt_get_global

Also,
- cleanly isolate all runtime data structure definitions shared by the
compiler and runtime into lib/runtime/CompilerDataStructures.h
2020-07-10 17:31:24 -07:00
Stella Laurenzo 2ba8296151 Add script tools/format_source.sh and run it on all python and c++ sources. 2020-06-13 14:53:54 -07:00
Sean Silva 3a09455540 Use upstream shape.from_extents
Replace our local `tcp.shape_from_extents` op with the upstream
`shape.from_extents` op.
2020-05-21 14:51:01 -07:00
Sean Silva 1fed1cb016 Update llvm-project to 753a21928413f8a7e76978cb1354e09150e114e0 2020-05-21 13:09:06 -07:00
Sean Silva 87aa561c69 Remove RtGetTensorExtentOp.
It is unused now, and will be superceded by a proper runtime dialect.
2020-05-21 10:17:49 -07:00
Sean Silva be1971c4fc Rename tcp.abort_if to tcp.shape_observe_error
This more clearly captures its semantics as a structural "observer" of
code that we currently mark as NoSideEffect but eventually lowers to
eager error handling code.

Also, update LowerRankedShapes to erase it, now that the layering here
is clear. That pass reifies the eager error handling code, so the need
for the dummy op to keep things alive isn't needed.

With this change, we are now ready to start lowering to LLVM!
This is the current print-ir-after-all from e2e-lowering-pipeline:
https://reviews.llvm.org/P8221
2020-05-18 13:38:47 -07:00
Sean Silva eaeb4011e6 Lower !shape.shape to SSA values.
This uses an approach inspired by what is done in IREE. See comments on
LowerRankedShapes.cpp for how it works.

The basic gist is that we have an op that creates a !shape.shape from a
set of SSA values representing the extents, and then iteratively replace
any op producing a !shape.shape with instances of that op.
2020-05-13 17:20:23 -07:00
Stella Laurenzo 950ba12426 Bump llvm-project to 3af85fa8f06220b43f03f26de216a67be4568fe7. 2020-05-08 20:42:40 -07:00
Sean Silva e29aef855b Initial TCF/TCP E2E seed.
Very much WIP.

This is enough to get tcf.add down to approximately the "linalg.generic
on buffers" level of abstraction. (but there are nuances)
2020-05-08 20:20:41 -07:00