llvm-capstone/mlir/docs/DataLayout.md

Data Layout Modeling

Data layout information allows the compiler to answer questions related to how a value of a particular type is stored in memory. For example, the size of a value or its address alignment requirements. It enables, among others, the generation of various linear memory addressing schemes for containers of abstract types and deeper reasoning about vectors.

The data layout subsystem is designed to scale to MLIR's open type and operation system. At the top level, it consists of:

• attribute interfaces that can be implemented by concrete data layout specifications;
• type interfaces that should be implemented by types subject to data layout;
• operation interfaces that must be implemented by operations that can serve as data layout scopes (e.g., modules);
• and dialect interfaces for data layout properties unrelated to specific types.

Built-in types are handled specially to decrease the overall query cost.

Usage

Scoping

Following MLIR's nested structure, data layout properties are scoped to regions belonging to specific operations that implement the DataLayoutOpInterface. Such scoping operations partially control the data layout properties and may have attributes that affect them, typically organized in a data layout specification.

Types may have a different data layout in different scopes, including scopes that are nested in other scopes such as modules contained in other modules. At the same time, within the given scope excluding any nested scope, a given type has fixed data layout properties. Types are also expected to have a default, "natural" data layout in case they are used outside of any operation that provides data layout scope for them. This ensure data layout queries always have a valid result.

Compatibility and Transformations

The information necessary to compute layout properties can be combined from nested scopes. For example, an outer scope can define layout properties for a subset of types while inner scopes define them for a disjoint subset, or scopes can progressively relax alignment requirements on a type. This mechanism is supported by the notion of data layout compatibility: the layout defined in a nested scope is expected to be compatible with that of the outer scope. MLIR does not prescribe what compatibility means for particular ops and types but provides hooks for them to provide target- and type-specific checks. For example, one may want to only allow relaxation of alignment constraints (i.e., smaller alignment) in nested modules or, alternatively, one may require nested modules to fully redefine all constraints of the outer scope.

Data layout compatibility is also relevant during IR transformation. Any transformation that affects the data layout scoping operation is expected to maintain data layout compatibility. It is under responsibility of the transformation to ensure it is indeed the case.

Queries

Data layout property queries can be performed on the special object -- DataLayout -- which can be created for the given scoping operation. These objects allow one to interface with the data layout infrastructure and query properties of given types in the scope of the object. The signature of DataLayout class is as follows.

class DataLayout {
public:
  explicit DataLayout(DataLayoutOpInterface scope);

  unsigned getTypeSize(Type type) const;
  unsigned getTypeABIAlignment(Type type) const;
  unsigned getTypePreferredAlignment(Type type) const;
};

The user can construct the DataLayout object for the scope of interest. Since the data layout properties are fixed in the scope, they will be computed only once upon first request and cached for further use. Therefore, DataLayout(op.getParentOfType<DataLayoutOpInterface>()).getTypeSize(type) is considered an anti-pattern since it discards the cache after use. Because of caching, a DataLayout object returns valid results as long as the data layout properties of enclosing scopes remain the same, that is, as long as none of the ancestor operations are modified in a way that affects data layout. After such a modification, the user is expected to create a fresh DataLayout object. To aid with this, DataLayout asserts that the scope remains identical if MLIR is compiled with assertions enabled.

Custom Implementations

Extensibility of the data layout modeling is provided through a set of MLIR Interfaces.

Data Layout Specifications

Data layout specification is an attribute that is conceptually a collection of key-value pairs called data layout specification entries. Data layout specification attributes implement the DataLayoutSpecInterface, described below. Each entry is itself an attribute that implements the DataLayoutEntryInterface. Entries have a key, either a Type or an Identifier, and a value. Keys are used to associate entries with specific types or dialects: when handling a data layout properties request, a type or a dialect can only see the specification entries relevant to them and must go through the supplied DataLayout object for any recursive query. This supports and enforces better composability because types cannot (and should not) understand layout details of other types. Entry values are arbitrary attributes, specific to the type.

For example, a data layout specification may be an actual list of pairs with simple custom syntax resembling the following:

#my_dialect.layout_spec<
  #my_dialect.layout_entry<!my_dialect.type, size=42>,
  #my_dialect.layout_entry<"my_dialect.endianness", "little">,
  #my_dialect.layout_entry<!my_dialect.vector, prefer_large_alignment>>

The exact details of the specification and entry attributes, as well as their syntax, are up to implementations.

We use the notion of type class throughout the data layout subsystem. It corresponds to the C++ class of the given type, e.g., IntegerType for built-in integers. MLIR does not have a mechanism to represent type classes in the IR. Instead, data layout entries contain specific instances of a type class, for example, IntegerType{signedness=signless, bitwidth=8} (or i8 in the IR) or IntegerType{signedness=unsigned, bitwidth=32} (or ui32 in the IR). When handling a data layout property query, a type class will be supplied with all entries with keys belonging to this type class. For example, IntegerType will see the entries for i8, si16 and ui32, but will not see those for f32 or memref<?xi32> (neither will MemRefType see the entry for i32). This allows for type-specific "interpolation" behavior where a type class can compute data layout properties of any specific type instance given properties of other instances. Using integers as an example again, their alignment could be computed by taking that of the closest from above integer type with power-of-two bitwidth.

[include "Interfaces/DataLayoutAttrInterface.md"]

Data Layout Scoping Operations

Operations that define a scope for data layout queries, and that can be used to create a DataLayout object, are expected to implement the DataLayoutOpInterface. Such ops must provide at least a way of obtaining the data layout specification. The specification need not be necessarily attached to the operation as an attribute and may be constructed on-the-fly; it is only fetched once per DataLayout object and cached. Such ops may also provide custom handlers for data layout queries that provide results without forwarding the queries down to specific types or post-processing the results returned by types in target- or scope-specific ways. These custom handlers make it possible for scoping operations to (re)define data layout properties for types without having to modify the types themselves, e.g., when types are defined in another dialect.

[include "Interfaces/DataLayoutOpInterface.md"]

Types with Data Layout

Type classes that intend to handle data layout queries themselves are expected to implement the DataLayoutTypeInterface. This interface provides overridable hooks for each data layout query. Each of these hooks is supplied with the type instance, a DataLayout object suitable for recursive queries, and a list of data layout queries relevant for the type class. It is expected to provide a valid result even if the list of entries is empty. These hooks do not have access to the operation in the scope of which the query is handled and should use the supplied entries instead.

[include "Interfaces/DataLayoutTypeInterface.md"]

Dialects with Data Layout Identifiers

For data layout entries that are not related to a particular type class, the key of the entry is an Identifier that belongs to some dialect. In this case, the dialect is expected to implement the DataLayoutDialectInterface. This dialect provides hooks for verifying the validity of the entry value attributes and for and the compatibility of nested entries.

Query Dispatch

The overall flow of a data layout property query is as follows.

• The user constructs a DataLayout at the given scope. The constructor fetches the data layout specification and combines it with those of enclosing scopes (layouts are expected to be compatible).
• The user calls DataLayout::query(Type ty).
• If DataLayout has a cached response, this response is returned immediately.
• Otherwise, the query is handed down by DataLayout to DataLayoutOpInterface::query(ty, *this, relevantEntries) where the relevant entries are computed as described above.
• Unless the query hook is reimplemented by the op interface, the query is handled further down to DataLayoutTypeInterface::query(dataLayout, relevantEntries) after casting ty to the type interface. If the type does not implement the interface, an unrecoverable fatal error is produced.
• The type is expected to always provide the response, which is returned up the call stack and cached by the DataLayout.

Default Implementation

The default implementation of the data layout interfaces directly handles queries for a subset of built-in types.

Built-in Types

The following describes the default properties of built-in types.

The size of built-in integers and floats in bytes is computed as ceildiv(bitwidth, 8). The ABI alignment of integer types with bitwidth below 64 and of the float types is the closest from above power-of-two number of bytes. The ABI alignment of integer types with bitwidth 64 and above is 4 bytes (32 bits).

The size of built-in vectors is computed by first rounding their number of elements in the innermost dimension to the closest power-of-two from above, then getting the total number of elements, and finally multiplying it with the element size. For example, vector<3xi32> and vector<4xi32> have the same size. So do vector<2x3xf32> and vector<2x4xf32>, but vector<3x4xf32> and vector<4x4xf32> have different sizes. The ABI and preferred alignment of vector types is computed by taking the innermost dimension of the vector, rounding it up to the closest power-of-two, taking a product of that with element size in bytes, and rounding the result up again to the closest power-of-two.

Note: these values are selected for consistency with the default data layout in LLVM, which MLIR assumed until the introduction of proper data layout modeling, and with the modeling of n-D vectors. They may change in the future.

DLTI Dialect

The DLTI dialect provides the attributes implementing DataLayoutSpecInterface and DataLayoutEntryInterface, as well as a dialect attribute that can be used to attach the specification to a given operation. The verifier of this attribute triggers those of the specification and checks the compatiblity of nested specifications.