Cranelift Meta Language Reference¶

The Cranelift meta language is used to define instructions for Cranelift. It is a domain specific language embedded in Rust.

Todo

Point to the Rust documentation of the meta crate here.

This document is very out-of-date. Instead, you can have a look at the work-in-progress documentation of the meta crate there: https://docs.rs/cranelift-codegen-meta/0.34.0/cranelift_codegen_meta/.

This document describes the Python modules that form the embedded DSL.

The meta language descriptions are Python modules under the cranelift-codegen/meta-python directory. The descriptions are processed in two steps:

1. The Python modules are imported. This has the effect of building static data structures in global values in the modules. These static data structures in the base and isa packages use the classes in the cdsl package to describe instruction sets and other properties.
2. The static data structures are processed to produce Rust source code and constant tables.

The main driver for this source code generation process is the cranelift-codegen/meta-python/build.py script which is invoked as part of the build process if anything in the cranelift-codegen/meta-python directory has changed since the last build.

Settings¶

Settings are used by the environment embedding Cranelift to control the details of code generation. Each setting is defined in the meta language so a compact and consistent Rust representation can be generated. Shared settings are defined in the base.settings module. Some settings are specific to a target ISA, and defined in a settings.py module under the appropriate cranelift-codegen/meta-python/isa/* directory.

Settings can take boolean on/off values, small numbers, or explicitly enumerated symbolic values.

All settings must belong to a group, represented by a SettingGroup object.

Normally, a setting group corresponds to all settings defined in a module. Such a module looks like this:

group = SettingGroup('example')

foo = BoolSetting('use the foo')
bar = BoolSetting('enable bars', True)
opt = EnumSetting('optimization level', 'Debug', 'Release')

group.close(globals())


Instruction descriptions¶

New instructions are defined as instances of the Instruction class. As instruction instances are created, they are added to the currently open InstructionGroup.

The basic Cranelift instruction set described in Cranelift IR Reference is defined by the Python module base.instructions. This module has a global value base.instructions.GROUP which is an InstructionGroup instance containing all the base instructions.

An instruction is defined with a set of distinct input and output operands which must be instances of the Operand class.

Cranelift uses two separate type systems for operand kinds and SSA values.

Type variables¶

Instruction descriptions can be made polymorphic by using cdsl.operands.Operand instances that refer to a type variable instead of a concrete value type. Polymorphism only works for SSA value operands. Other operands have a fixed operand kind.

If multiple operands refer to the same type variable they will be required to have the same concrete type. For example, this defines an integer addition instruction:

Int = TypeVar('Int', 'A scalar or vector integer type', ints=True, simd=True)
a = Operand('a', Int)
x = Operand('x', Int)
y = Operand('y', Int)



The type variable Int is allowed to vary over all scalar and vector integer value types, but in a given instance of the iadd instruction, the two operands must have the same type, and the result will be the same type as the inputs.

There are some practical restrictions on the use of type variables, see Restricted polymorphism.

Immediate operands¶

Immediate instruction operands don’t correspond to SSA values, but have values that are encoded directly in the instruction. Immediate operands don’t have types from the cdsl.types.ValueType type system; they often have enumerated values of a specific type. The type of an immediate operand is indicated with an instance of ImmediateKind.

Entity references¶

Instruction operands can also refer to other entities in the same function. This can be extended basic blocks, or entities declared in the function preamble.

Value types¶

Concrete value types are represented as instances of ValueType. There are subclasses to represent scalar and vector types.

There are no predefined vector types, but they can be created as needed with the LaneType.by() function.

Instruction representation¶

The Rust in-memory representation of instructions is derived from the instruction descriptions. Part of the representation is generated, and part is written as Rust code in the cranelift.instructions module. The instruction representation depends on the input operand kinds and whether the instruction can produce multiple results.

Since all SSA value operands are represented as a Value in Rust code, value types don’t affect the representation.

When an instruction description is created, it is automatically assigned a predefined instruction format which is an instance of InstructionFormat.

Restricted polymorphism¶

The instruction format strictly controls the kinds of operands on an instruction, but it does not constrain value types at all. A given instruction description typically does constrain the allowed value types for its value operands. The type variables give a lot of freedom in describing the value type constraints, in practice more freedom than what is needed for normal instruction set architectures. In order to simplify the Rust representation of value type constraints, some restrictions are imposed on the use of type variables.

A polymorphic instruction has a single controlling type variable. For a given opcode, this type variable must be the type of the first result or the type of the input value operand designated by the typevar_operand argument to the InstructionFormat constructor. By default, this is the first value operand, which works most of the time.

The value types of instruction results must be one of the following:

1. A concrete value type.
2. The controlling type variable.
3. A type variable derived from the controlling type variable.

This means that all result types can be computed from the controlling type variable.

Input values to the instruction are allowed a bit more freedom. Input value types must be one of:

1. A concrete value type.
2. The controlling type variable.
3. A type variable derived from the controlling type variable.
4. A free type variable that is not used by any other operands.

This means that the type of an input operand can either be computed from the controlling type variable, or it can vary independently of the other operands.

Encodings¶

Encodings describe how Cranelift instructions are mapped to binary machine code for the target architecture. After the legalization pass, all remaining instructions are expected to map 1-1 to native instruction encodings. Cranelift instructions that can’t be encoded for the current architecture are called illegal instructions.

Some instruction set architectures have different CPU modes with incompatible encodings. For example, a modern ARMv8 CPU might support three different CPU modes: A64 where instructions are encoded in 32 bits, A32 where all instructions are 32 bits, and T32 which has a mix of 16-bit and 32-bit instruction encodings. These are incompatible encoding spaces, and while an iadd instruction can be encoded in 32 bits in each of them, it’s not the same 32 bits. It’s a judgement call if CPU modes should be modelled as separate targets, or as sub-modes of the same target. In the ARMv8 case, the different register banks means that it makes sense to model A64 as a separate target architecture, while A32 and T32 are CPU modes of the 32-bit ARM target.

In a given CPU mode, there may be multiple valid encodings of the same instruction. Both RISC-V and ARMv8’s T32 mode have 32-bit encodings of all instructions with 16-bit encodings available for some opcodes if certain constraints are satisfied.

Encodings are guarded by sub-target predicates. For example, the RISC-V “C” extension which specifies the compressed encodings may not be supported, and a predicate would be used to disable all of the 16-bit encodings in that case. This can also affect whether an instruction is legal. For example, x86 has a predicate that controls the SSE 4.1 instruction encodings. When that predicate is false, the SSE 4.1 instructions are not available.

Encodings also have a instruction predicate which depends on the specific values of the instruction’s immediate fields. This is used to ensure that immediate address offsets are within range, for example. The instructions in the base Cranelift instruction set can often represent a wider range of immediates than any specific encoding. The fixed-size RISC-style encodings tend to have more range limitations than CISC-style variable length encodings like x86.

The diagram below shows the relationship between the classes involved in specifying instruction encodings:

An Encoding instance specifies the encoding of a concrete instruction. The following properties are used to select instructions to be encoded:

• An opcode, i.e. iadd_imm, that must match the instruction’s opcode.
• Values for any type variables if the opcode represents a polymorphic instruction.
• An instruction predicate that must be satisfied by the instruction’s immediate operands.
• The CPU mode that must be active.
• A sub-target predicate that must be satisfied by the currently active sub-target.

An encoding specifies an encoding recipe along with some encoding bits that the recipe can use for native opcode fields etc. The encoding recipe has additional constraints that must be satisfied:

The additional predicates in the EncRecipe are merged with the per-encoding predicates when generating the encoding matcher code. Often encodings only need the recipe predicates.

Register constraints¶

After an encoding recipe has been chosen for an instruction, it is the register allocator’s job to make sure that the recipe’s Register constraints are satisfied. Most ISAs have separate integer and floating point registers, and instructions can usually only use registers from one of the banks. Some instruction encodings are even more constrained and can only use a subset of the registers in a bank. These constraints are expressed in terms of register classes.

Sometimes the result of an instruction is placed in a register that must be the same as one of the input registers. Some instructions even use a fixed register for inputs or results.

Each encoding recipe specifies separate constraints for its value operands and result. These constraints are separate from the instruction predicate which can only evaluate the instruction’s immediate operands.

Register class constraints¶

The most common type of register constraint is the register class. It specifies that an operand or result must be allocated one of the registers from the given register class:

IntRegs = RegBank('IntRegs', ISA, 'General purpose registers', units=16, prefix='r')
GPR = RegClass(IntRegs)
R = EncRecipe('R', Binary, ins=(GPR, GPR), outs=GPR)


This defines an encoding recipe for the Binary instruction format where both input operands must be allocated from the GPR register class.

Tied register operands¶

In more compact machine code encodings, it is common to require that the result register is the same as one of the inputs. This is represented with tied operands:

CR = EncRecipe('CR', Binary, ins=(GPR, GPR), outs=0)


This indicates that the result value must be allocated to the same register as the first input value. Tied operand constraints can only be used for result values, so the number always refers to one of the input values.

Fixed register operands¶

Some instructions use hard-coded input and output registers for some value operands. An example is the pblendvb x86 SSE instruction which takes one of its three value operands in the hard-coded %xmm0 register:

XMM0 = FPR[0]
SSE66_XMM0 = EncRecipe('SSE66_XMM0', Ternary, ins=(FPR, FPR, XMM0), outs=0)


The syntax FPR[0] selects the first register from the FPR register class which consists of all the XMM registers.

Stack operands¶

Cranelift’s register allocator can assign an SSA value to a stack slot if there isn’t enough registers. It will insert spill and fill instructions as needed to satisfy instruction operand constraints, but it is also possible to have instructions that can access stack slots directly:

CSS = EncRecipe('CSS', Unary, ins=GPR, outs=Stack(GPR))


An output stack value implies a store to the stack, an input value implies a load.

Targets¶

Cranelift can be compiled with support for multiple target instruction set architectures. Each ISA is represented by a cdsl.isa.TargetISA instance.

The definitions for each supported target live in a package under cranelift-codegen/meta-python/isa.

Glossary¶

Illegal instruction
An instruction is considered illegal if there is no encoding available for the current CPU mode. The legality of an instruction depends on the value of sub-target predicates, so it can’t always be determined ahead of time.
CPU mode
Every target defines one or more CPU modes that determine how the CPU decodes binary instructions. Some CPUs can switch modes dynamically with a branch instruction (like ARM/Thumb), while other modes are process-wide (like x86 32/64-bit).
Sub-target predicate
A predicate that depends on the current sub-target configuration. Examples are “Use SSE 4.1 instructions”, “Use RISC-V compressed encodings”. Sub-target predicates can depend on both detected CPU features and configuration settings.
Instruction predicate
A predicate that depends on the immediate fields of an instruction. An example is “the load address offset must be a 10-bit signed integer”. Instruction predicates do not depend on the registers selected for value operands.
Register constraint
Value operands and results correspond to machine registers. Encodings may constrain operands to either a fixed register or a register class. There may also be register constraints between operands, for example some encodings require that the result register is one of the input registers.