This revision refactors the usage of multithreaded utilities in MLIR to use a common
thread pool within the MLIR context, in addition to a new utility that makes writing
multi-threaded code in MLIR less error prone. Using a unified thread pool brings about
several advantages:
* Better thread usage and more control
We currently use the static llvm threading utilities, which do not allow multiple
levels of asynchronous scheduling (even if there are open threads). This is due to
how the current TaskGroup structure works, which only allows one truly multithreaded
instance at a time. By having our own ThreadPool we gain more control and flexibility
over our job/thread scheduling, and in a followup can enable threading more parts of
the compiler.
* The static nature of TaskGroup causes issues in certain configurations
Due to the static nature of TaskGroup, there have been quite a few problems related to
destruction that have caused several downstream projects to disable threading. See
D104207 for discussion on some related fallout. By having a ThreadPool scoped to
the context, we don't have to worry about destruction and can ensure that any
additional MLIR thread usage ends when the context is destroyed.
Differential Revision: https://reviews.llvm.org/D104516
This changes the outer verification loop to not recurse into
IsolatedFromAbove operations - instead return them up to a place
where a parallel for loop can process them all in parallel. This
also changes Dominance checking to happen on IsolatedFromAbove
chunks of the region tree, which makes it easy to fold operation
and dominance verification into a single simple parallel regime.
This speeds up firtool in CIRCT from ~40s to 31s on a large
testcase in -verify-each mode (the default). The .fir parser and
module passes in particular benefit from this - FModule passes
(roughly analogous to function passes) were already running the
verifier in parallel as part of the pass manager. This allows
the whole-module passes to verify their enclosed functions /
FModules in parallel.
-verify-each mode is still faster (26.3s on the same testcase),
but we do expect the verifier to take *some* time.
Differential Revision: https://reviews.llvm.org/D104207
This reverts commit 08664d005c, which according to
https://reviews.llvm.org/D103373 was pushed accidentally, and I believe it
causes timeouts in some internal mlir tests.
One of the key algorithms used in the "mlir::verify(op)" method is the
dominance checker, which ensures that operand values properly dominate
the operations that use them.
The MLIR dominance implementation has a number of algorithmic problems,
and is not really set up in general to answer dense queries: it's constant
factors are really slow with multiple map lookups and scans, even in the
easy cases. Furthermore, when calling mlir::verify(module) or some other
high level operation, it makes sense to parallelize the dominator
verification of all the functions within the module.
This patch has a few changes to enact this:
1) It splits dominance checking into "IsolatedFromAbove" units. Instead
of building a monolithic DominanceInfo for everything in a module,
for example, it checks dominance for the module to all the functions
within it (noop, since there are no operands at this level) then each
function gets their own DominanceInfo for each of their scope.
2) It adds the ability for mlir::DominanceInfo (and post dom) to be
constrained to an IsolatedFromAbove region. There is no reason to
recurse into IsolatedFromAbove regions since use/def relationships
can't span this region anyway. This is already checked by the time
the verifier gets here.
3) It avoids querying DominanceInfo for trivial checks (e.g. intra Block
references) to eliminate constant factor issues).
4) It switches to lazily constructing DominanceInfo because the trivial
check case handles the vast majority of the cases and avoids
constructing DominanceInfo entirely in some cases (e.g. at the module
level or for many Regions's that contain a single Block).
5) It parallelizes analysis of collections IsolatedFromAbove operations,
e.g. each of the functions within a Module.
All together this is more than a 10% speedup on `firtool` in circt on a
large design when run in -verify-each mode (our default) since the verifier
is invoked after each pass.
Still todo is to parallelize the main verifier pass. I decided to split
this out to its own thing since this patch is already large-ish.
Differential Revision: https://reviews.llvm.org/D103373
This tidies up the code a bit:
* Eliminate the ctx member, which doesn't need to be stored.
* Rename verify(Operation) to make it more clear that it is
doing more than verifyOperation and that the dominance check
isn't being done multiple times.
* Rename mayNotHaveTerminator which was confusing about whether
it wasn't known whether it had a terminator, when it is really
about whether it is legal to have a terminator.
* Some minor optimizations: don't check for RegionKindInterface
if there are no regions. Don't do two passes over the
operations in a block in OperationVerifier::verifyDominance when
one will do.
The optimizations are actually a measurable (but minor) win in some
CIRCT cases.
Differential Revision: https://reviews.llvm.org/D101267
In particular for Graph Regions, the terminator needs is just a
historical artifact of the generalization of MLIR from CFG region.
Operations like Module don't need a terminator, and before Module
migrated to be an operation with region there wasn't any needed.
To validate the feature, the ModuleOp is migrated to use this trait and
the ModuleTerminator operation is deleted.
This patch is likely to break clients, if you're in this case:
- you may iterate on a ModuleOp with `getBody()->without_terminator()`,
the solution is simple: just remove the ->without_terminator!
- you created a builder with `Builder::atBlockTerminator(module_body)`,
just use `Builder::atBlockEnd(module_body)` instead.
- you were handling ModuleTerminator: it isn't needed anymore.
- for generic code, a `Block::mayNotHaveTerminator()` may be used.
Differential Revision: https://reviews.llvm.org/D98468
This also exposed a bug in Dialect loading where it was not correctly identifying identifiers that had the dialect namespace as a prefix.
Differential Revision: https://reviews.llvm.org/D97431
These properties were useful for a few things before traits had a better integration story, but don't really carry their weight well these days. Most of these properties are already checked via traits in most of the code. It is better to align the system around traits, and improve the performance/cost of traits in general.
Differential Revision: https://reviews.llvm.org/D96088
- When a block is not empty and does not end with a terminator, flag the error on the
last operation of the block instead of the start of the block.
Differential Revision: https://reviews.llvm.org/D90988
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
registry.insert<mlir::standalone::StandaloneDialect>();
registry.insert<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
Differential Revision: https://reviews.llvm.org/D85622
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
registry.insert<mlir::standalone::StandaloneDialect>();
registry.insert<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
Differential Revision: https://reviews.llvm.org/D85622
This changes the behavior of constructing MLIRContext to no longer load globally
registered dialects on construction. Instead Dialects are only loaded explicitly
on demand:
- the Parser is lazily loading Dialects in the context as it encounters them
during parsing. This is the only purpose for registering dialects and not load
them in the context.
- Passes are expected to declare the dialects they will create entity from
(Operations, Attributes, or Types), and the PassManager is loading Dialects into
the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only
need to load the dialect for the IR it will emit, and the optimizer is
self-contained and load the required Dialects. For example in the Toy tutorial,
the compiler only needs to load the Toy dialect in the Context, all the others
(linalg, affine, std, LLVM, ...) are automatically loaded depending on the
optimization pipeline enabled.
To adjust to this change, stop using the existing dialect registration: the
global registry will be removed soon.
1) For passes, you need to override the method:
virtual void getDependentDialects(DialectRegistry ®istry) const {}
and registery on the provided registry any dialect that this pass can produce.
Passes defined in TableGen can provide this list in the dependentDialects list
field.
2) For dialects, on construction you can register dependent dialects using the
provided MLIRContext: `context.getOrLoadDialect<DialectName>()`
This is useful if a dialect may canonicalize or have interfaces involving
another dialect.
3) For loading IR, dialect that can be in the input file must be explicitly
registered with the context. `MlirOptMain()` is taking an explicit registry for
this purpose. See how the standalone-opt.cpp example is setup:
mlir::DialectRegistry registry;
mlir::registerDialect<mlir::standalone::StandaloneDialect>();
mlir::registerDialect<mlir::StandardOpsDialect>();
Only operations from these two dialects can be in the input file. To include all
of the dialects in MLIR Core, you can populate the registry this way:
mlir::registerAllDialects(registry);
4) For `mlir-translate` callback, as well as frontend, Dialects can be loaded in
the context before emitting the IR: context.getOrLoadDialect<ToyDialect>()
This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand:
- the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context.
- Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled.
Differential Revision: https://reviews.llvm.org/D85622
This changes the behavior of constructing MLIRContext to no longer load globally registered dialects on construction. Instead Dialects are only loaded explicitly on demand:
- the Parser is lazily loading Dialects in the context as it encounters them during parsing. This is the only purpose for registering dialects and not load them in the context.
- Passes are expected to declare the dialects they will create entity from (Operations, Attributes, or Types), and the PassManager is loading Dialects into the Context when starting a pipeline.
This changes simplifies the configuration of the registration: a compiler only need to load the dialect for the IR it will emit, and the optimizer is self-contained and load the required Dialects. For example in the Toy tutorial, the compiler only needs to load the Toy dialect in the Context, all the others (linalg, affine, std, LLVM, ...) are automatically loaded depending on the optimization pipeline enabled.
Some dialects have semantics which is not well represented by common
SSA structures with dominance constraints. This patch allows
operations to declare the 'kind' of their contained regions.
Currently, two kinds are allowed: "SSACFG" and "Graph". The only
difference between them at the moment is that SSACFG regions are
required to have dominance, while Graph regions are not required to
have dominance. The intention is that this Interface would be
generated by ODS for existing operations, although this has not yet
been implemented. Presumably, if someone were interested in code
generation, we might also have a "CFG" dialect, which defines control
flow, but does not require SSA.
The new behavior is mostly identical to the previous behavior, since
registered operations without a RegionKindInterface are assumed to
contain SSACFG regions. However, the behavior has changed for
unregistered operations. Previously, these were checked for
dominance, however the new behavior allows dominance violations, in
order to allow the processing of unregistered dialects with Graph
regions. One implication of this is that regions in unregistered
operations with more than one op are no longer CSE'd (since it
requires dominance info).
I've also reorganized the LangRef documentation to remove assertions
about "sequential execution", "SSA Values", and "Dominance". Instead,
the core IR is simply "ordered" (i.e. totally ordered) and consists of
"Values". I've also clarified some things about how control flow
passes between blocks in an SSACFG region. Control Flow must enter a
region at the entry block and follow terminator operation successors
or be returned to the containing op. Graph regions do not define a
notion of control flow.
see discussion here:
https://llvm.discourse.group/t/rfc-allowing-dialects-to-relax-the-ssa-dominance-condition/833/53
Differential Revision: https://reviews.llvm.org/D80358
It is possible for optimizations to create SSA code which violates
the dominance property in unreachable blocks. Equivalently, dominance
computed using normal mechanisms is undefined in unreachable blocks.
See discussion here: https://llvm.discourse.group/t/rfc-allowing-dialects-to-relax-the-ssa-dominance-condition/833/51
This patch only checks the dominance condition inside blocks which are
reachable from the the entry block of their region. Note that the
dominance conditions of regions contained in an unreachable block are
still checked.
Differential Revision: https://reviews.llvm.org/D79922
These libraries are distinct from other things in Analysis in that they
operate only on core IR concepts. This also simplifies dependencies
so that Dialect -> Analysis -> Parser -> IR. Previously, the parser depended
on portions of the the Analysis directory as well, which sometimes
caused issues with the way the cmake makefile generator discovers
dependencies on generated files during compilation.
Differential Revision: https://reviews.llvm.org/D79240
Mehdi Amini