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
The indices for insert/compress were previously provided as
a memref<?xindex> with proper rank, since that matched the
argument for the runtime support libary better. However, with
proper codegen coming, providing the indices as SSA values
is much cleaner. This also brings the sparse_tensor.insert
closer to unification with tensor.insert, planned in the
longer run.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D134404
This change goes not impact any semantics yet, but it
is in preparation for implementing the unordered and not-unique
properties. Changing lex_insert to insert is a first step.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D133531
The "sparsification" pass does not need the ability to use runtime values for
the dimension, so the only source for variability would have been user code.
Restricting the dimension to constants simplifies code generation.
Reviewed By: Peiming, wrengr
Differential Revision: https://reviews.llvm.org/D133458
This change omits default values from the sparse tensor type,
saving considerable text real estate for the common cases.
Reviewed By: Peiming
Differential Revision: https://reviews.llvm.org/D132083
This op used to belong to the sparse dialect, but there are use cases for dense bufferization as well. (E.g., when a tensor alloc is returned from a function and should be deallocated at the call site.) This change moves the op to the bufferization dialect, which now has an `alloc_tensor` and a `dealloc_tensor` op.
Differential Revision: https://reviews.llvm.org/D129985
When the iteration graph is cyclic (even after several attempts using less and less constraints), the current sparse compiler bails out, and no rewriting hapens. However, this revision adds some new logic where the sparse compiler tries to find a single input sparse tensor that breaks the cycle, and then adds a proper sparse conversion operation. This way, more incoming kernels can be handled!
Note, the resulting code is not optimal (although it keeps more or less proper "sparse" complexity), and more improvements should be added (especially when the kernel directly yields without computation, such as the transpose example). However, handling is better than not handling ;-)
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D128847
