The new class helps encapsulate the arguments to `_mlir_ciface_newSparseTensor` so that client code doesn't depend on the details of the API. (This makes way for the next differential which significantly alters the API.)
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D137680
This revision generalizes lowering the sparse_tensor.insert op into actual code that directly operates on the memrefs of a sparse storage scheme. The current insertion strategy does *not* rely on a cursor anymore, with introduces some testing overhead for each insertion (but still proportional to the rank, as before). Over time, we can optimize the code generation, but this version enables us to finish the effort to migrate from library to actual codegen.
Things to do:
(1) carefully deal with (un)ordered and (not)unique
(2) omit overhead when not needed
(3) optimize and specialize
(4) try to avoid the pointer "cleanup" (at HasInserts), and make sure the storage scheme is consistent at every insertion point (so that it can "escape" without concerns).
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D137457
This patch re-commit D137468 and D137463, which were reverted by mistakes.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D137579
This patch fix the re-revert D135927 (which caused a windows build failure) to re-enable parallel for/reduction. It also fix a warning caused by D137442.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D137565
This reverts commit 53d5d3401120f2aa741a73a5a9ba0ce012ca532c.
This is causing a build failure on the windows mlir bot that was previously hidden by another sparse tensor change that caused failures:
https://lab.llvm.org/buildbot/#/builders/13/builds/28006
This reverts commit 70508b614e6478ba2c3fc79e935e2c68e2d79b71.
This change depends on a reverted change that broke the windows mlir buildbot; reverting to bring remaining mlir bots to green
Replace the quick sort partition method with one that is more similar to the
method used by C++ std quick sort. This improves the runtime for sorting
sk_2005.mtx by more than 10x.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D137290
- argument name 'isLastOutput' in comment does not match parameter name
'hasOutput'.
- override is redundant since the function is already declared 'final'.
The alloc->insert/compress->load chain needs to be
properly represented with an SSA chain now in loops
and if statements to properly reflect the modifying
behavior (runtime support lib is forgiving on breaking
this, but the new codegen is not).
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D136966
This prepare a subsequent revision that will generalize
the insertion code generation. Similar to the support lib,
insertions become much easier to perform with some "cursor"
bookkeeping. Note that we, in the long run, could perhaps
avoid storing the "cursor" permanently and use some
retricted-scope solution (alloca?) instead. However,
that puts harder restrictions on insertion-chain operations,
so for now we follow the more straightforward approach.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D136800
Also fix the rewrite rule for sparse_tensor.new to reflect the recent change of
the runtime C interface and to use utilities for memref.alloca.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D135891
Outline the code that generates the loop structure to iterate over a dense
tensor or a sparse constant to genDenseTensorOrSparseConstantIterLoop.
Move a few routines to CodegenUtils for sharing.
Reviewed By: wrengr
Differential Revision: https://reviews.llvm.org/D136210
Previously, it used DimLevelType::SingletonNo to represent an unorder COO
tensor of rank 1 while it should use DimLevelType::CompressedNuNo.
Reviewed By: Peiming, wrengr
Differential Revision: https://reviews.llvm.org/D136387
This is to allow the use of a nop convert to express that the sparse tensor
allocated through bufferization::AllocTensorOp will be expanded to sparse
tensor storage by sparse tensor codegen.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D136214
This removes another massive source of redundancy, and instead has the Merger.{h,cpp} reuse the SparseTensorEnums library.
Depends On D136005
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D136123
Move the SparseTensorEnums library out of the ExecutionEngine directory and into Dialect/SparseTensor/IR.
Depends On D136002
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D136005
This differential splits the SparseTensorEnums library out from the SparseTensorRuntime library. The actual moving of files will be handled in the next differential.
Depends On D135996
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D136002
builds SSA cycle for compress insertion loop
adds casting on index mismatch during push_back
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D136186
This differential replaces all uses of SparseTensorEncodingAttr::DimLevelType with DimLevelType. The next differential will break out a separate library for the DimLevelType enum, so that the Dialect code doesn't need to depend on the rest of the runtime
Depends On D135995
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D135996
This change is to make way for reusing the DimLevelType enum in lieu of the SparseTensorEncodingAttr::DimLevelType enum, but broken out to make it quick and easy to review
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D135995
This is a proof of concept insertion implementation that sets up
the basic framework and implements it with push backs for just
sparse vectors. It adds insertion/compression through SSA values,
so that we properly update the memref after after pushback operation.
Note that properly using SSA values in sparsification is still TBD
but I will wait until Peiming's loop emitter is in to avoid conflicts.
Reviewed By: wrengr
Differential Revision: https://reviews.llvm.org/D136008
