TritonGPUOps¶

`triton_gpu.async_commit_group` (triton::gpu::AsyncCommitGroupOp)¶

Async commit group

Syntax:

operation ::= `triton_gpu.async_commit_group` $inputTokens attr-dict

Traits: VerifyTensorLayoutsTrait

Interfaces: InferTypeOpInterface

Operands:¶

Operand	Description
`inputTokens`	variadic of async token type

Results:¶

Result	Description
`asyncToken`	async token type

`triton_gpu.async_copy_global_to_local` (triton::gpu::AsyncCopyGlobalToLocalOp)¶

Copy data from global memory to local memory asynchronously

Syntax:

operation ::= `triton_gpu.async_copy_global_to_local` $src `,` $result (`mask` $mask^)? (`other` $other^)?
              oilist(`cacheModifier` `=` $cache | `evictionPolicy` `=` $evict)
              attr-dict `:` type($src) `->` type($result)

This operation copies data from global memory to local memory asynchronously. This is analogue to tt.load except the data are copied to local memory pointed by by the memory descriptor instread of a distributed tensor. The rest of the operands are the same as tt.load.

Traits: AttrSizedOperandSegments, VerifyTensorLayoutsTrait

Interfaces: InferTypeOpInterface, MemoryEffectOpInterface (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{MemoryEffects::Read on ::mlir::triton::GlobalMemory, MemoryEffects::Write on ::mlir::triton::gpu::SharedMemory}

Attributes:¶

Attribute	MLIR Type	Description
`cache`	::mlir::triton::CacheModifierAttr	allowed 32-bit signless integer cases: 1, 2, 3, 4, 5, 6 {{% markdown %}}Enum cases: * none (`NONE`) * ca (`CA`) * cg (`CG`) * wb (`WB`) * cs (`CS`) * wt (`WT`){{% /markdown %}}
`evict`	::mlir::triton::EvictionPolicyAttr	allowed 32-bit signless integer cases: 1, 2, 3 {{% markdown %}}Enum cases: * evict_normal (`NORMAL`) * evict_first (`EVICT_FIRST`) * evict_last (`EVICT_LAST`){{% /markdown %}}
`isVolatile`	::mlir::BoolAttr	bool attribute

Operands:¶

Operand	Description
`src`	ranked tensor of ptr values
`result`	memory descriptor type (`::mlir::triton::MemDescType`) in Triton IR type system
`mask`	tensor of 1-bit signless integer values
`other`	floating-point or ranked tensor of floating-point values or integer or ranked tensor of integer values or ptr or ranked tensor of ptr values or ptr

Results:¶

Result	Description
`token`	async token type

`triton_gpu.async_wait` (triton::gpu::AsyncWaitOp)¶

Async wait

Syntax:

operation ::= `triton_gpu.async_wait` $asyncToken attr-dict

Traits: VerifyTensorLayoutsTrait

Interfaces: InferTypeOpInterface

Attributes:¶

Attribute	MLIR Type	Description
`num`	::mlir::IntegerAttr	32-bit signless integer attribute

Operands:¶

Operand	Description
`asyncToken`	variadic of async token type

Results:¶

Result	Description
`retToken`	async token type

`triton_gpu.convert_layout` (triton::gpu::ConvertLayoutOp)¶

Convert layout

Syntax:

operation ::= `triton_gpu.convert_layout` $src attr-dict `:` type($src) `->` type($result)

Traits: AlwaysSpeculatableImplTrait, SameOperandsAndResultElementType, SameOperandsAndResultShape, VerifyTensorLayoutsTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Operands:¶

Operand	Description
`src`	ranked tensor of floating-point or integer or ptr values

Results:¶

Result	Description
`result`	ranked tensor of floating-point or integer or ptr values

`triton_gpu.local_alloc` (triton::gpu::LocalAllocOp)¶

Allocate tensor

Syntax:

operation ::= `triton_gpu.local_alloc` $src attr-dict `:` functional-type(operands, results)

This operation allocates buffer in shared memory and return a descriptor containing the address and a view of the buffer.

Explicitly deallocating a buffer is optional; see local_dealloc.

Traits: VerifyTensorLayoutsTrait

Interfaces: MemoryEffectOpInterface

Operands:¶

Operand	Description
`src`	ranked tensor of floating-point or integer or ptr values

Results:¶

Result	Description
`result`	memory descriptor type (`::mlir::triton::MemDescType`) in Triton IR type system

`triton_gpu.local_dealloc` (triton::gpu::LocalDeallocOp)¶

Dealloc buffer

Syntax:

operation ::= `triton_gpu.local_dealloc` $src attr-dict `:` qualified(type($src))

This operation deallocates a buffer explicitly. Using the buffer after this operation is undefined.

This operation is optional. If you don’t explicitly dealloc a buffer, the compiler assumes it’s deallocated at the first point that post-dominates all uses of the alloc.

Because we assume a memdesc is dead at the first point that post-dominates its uses, ops that wait for an async operation on a memdesc to complete (such as triton_nvidia_gpu.dot_wait) should also take the memdesc as an operand.

Traits: VerifyTensorLayoutsTrait

Interfaces: MemoryEffectOpInterface (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{MemoryEffects::Free on ::mlir::triton::gpu::SharedMemory}

Operands:¶

Operand	Description
`src`	memory descriptor type (`::mlir::triton::MemDescType`) in Triton IR type system

`triton_gpu.local_load` (triton::gpu::LocalLoadOp)¶

Load a buffer from local memory into a distributed tensor

Syntax:

operation ::= `triton_gpu.local_load` $src (`token` $token^)? attr-dict `:` qualified(type($src)) `->` type($result)

Load a tensor from the local memory descriptor into a distributed tensor.

Traits: VerifyTensorLayoutsTrait

Interfaces: MemoryEffectOpInterface (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{MemoryEffects::Read on ::mlir::triton::gpu::SharedMemory}

Operands:¶

Operand	Description
`src`	memory descriptor type (`::mlir::triton::MemDescType`) in Triton IR type system
`token`	async token type

Results:¶

Result	Description
`result`	ranked tensor of floating-point or integer or ptr values

`triton_gpu.memdesc_subview` (triton::gpu::MemDescSubviewOp)¶

Take a subview of the descriptor.

Syntax:

operation ::= `triton_gpu.memdesc_subview` $src `[` $offsets `]` attr-dict `:` qualified(type($src)) `->` qualified(type($result))

This operation returns a new descriptor representing a subview of the buffer. It doesn’t affect the underlying memory. The subview can be rank-reduced.

For example, suppose that

the input shape is 2x4x16xf16,
the output shape is 4x4xf16, and
offsets = [1, 0, 4].

Then in Python syntax, the subview covers input[1][0:4][4:8].

Traits: AlwaysSpeculatableImplTrait, VerifyTensorLayoutsTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Operands:¶

Operand	Description
`src`	memory descriptor type (`::mlir::triton::MemDescType`) in Triton IR type system
`offsets`	variadic of 32-bit signless integer

Results:¶

Result	Description
`result`	memory descriptor type (`::mlir::triton::MemDescType`) in Triton IR type system

TritonGPUOps¶

triton_gpu.async_commit_group (triton::gpu::AsyncCommitGroupOp)¶

Operands:¶

Results:¶

triton_gpu.async_copy_global_to_local (triton::gpu::AsyncCopyGlobalToLocalOp)¶

Attributes:¶

Operands:¶

Results:¶

triton_gpu.async_wait (triton::gpu::AsyncWaitOp)¶

Attributes:¶

Operands:¶

Results:¶

triton_gpu.convert_layout (triton::gpu::ConvertLayoutOp)¶

Operands:¶

Results:¶

triton_gpu.local_alloc (triton::gpu::LocalAllocOp)¶

Operands:¶

Results:¶

triton_gpu.local_dealloc (triton::gpu::LocalDeallocOp)¶

Operands:¶

triton_gpu.local_load (triton::gpu::LocalLoadOp)¶

Operands:¶

Results:¶

triton_gpu.memdesc_subview (triton::gpu::MemDescSubviewOp)¶

Operands:¶

Results:¶

`triton_gpu.async_commit_group` (triton::gpu::AsyncCommitGroupOp)¶

`triton_gpu.async_copy_global_to_local` (triton::gpu::AsyncCopyGlobalToLocalOp)¶

`triton_gpu.async_wait` (triton::gpu::AsyncWaitOp)¶

`triton_gpu.convert_layout` (triton::gpu::ConvertLayoutOp)¶

`triton_gpu.local_alloc` (triton::gpu::LocalAllocOp)¶

`triton_gpu.local_dealloc` (triton::gpu::LocalDeallocOp)¶

`triton_gpu.local_load` (triton::gpu::LocalLoadOp)¶

`triton_gpu.memdesc_subview` (triton::gpu::MemDescSubviewOp)¶