'nvvm' Dialect

Operations ¶

source

nvvm.bar.warp.sync (NVVM::SyncWarpOp) ¶

Syntax:

operation ::= `nvvm.bar.warp.sync` $mask attr-dict `:` type($mask)

Operands: ¶

nvvm.barrier (NVVM::BarrierOp) ¶

Syntax:

operation ::= `nvvm.barrier` (`id` `=` $barrierId^)? (`number_of_threads` `=` $numberOfThreads^)? attr-dict

Traits: AttrSizedOperandSegments

Operands: ¶

nvvm.barrier.arrive (NVVM::BarrierArriveOp) ¶

Syntax:

operation ::= `nvvm.barrier.arrive` (`id` `=` $barrierId^)? `number_of_threads` `=` $numberOfThreads attr-dict

Thread that executes this op announces their arrival at the barrier with given id and continue their execution.

The default barrier id is 0 that is similar to nvvm.barrier Op. When barrierId is not present, the default barrier id is used.

[For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-bar)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.barrier0 (NVVM::Barrier0Op) ¶

Syntax:

operation ::= `nvvm.barrier0` attr-dict

nvvm.cluster.arrive (NVVM::ClusterArriveOp) ¶

Cluster Barrier Arrive Op

Syntax:

operation ::= `nvvm.cluster.arrive` attr-dict

The cluster.arrive can be used by the threads within the cluster for synchronization and communication. The cluster.arrive instruction marks the warps’ arrival at the barrier without causing the executing thread to wait for other participating threads.

The aligned attribute, when provided, generates the .aligned version of the PTX instruction.

[For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-barrier-cluster)

Attributes: ¶

nvvm.cluster.arrive.relaxed (NVVM::ClusterArriveRelaxedOp) ¶

Cluster Barrier Relaxed Arrive Op

Syntax:

operation ::= `nvvm.cluster.arrive.relaxed` attr-dict

The cluster.arrive can be used by the threads within the cluster for synchronization and communication. The cluster.arrive instruction marks the warps’ arrival at the barrier without causing the executing thread to wait for other participating threads.

The aligned attribute, when provided, generates the .aligned version of the PTX instruction. The .relaxed qualifier on cluster.arrive specifies that there are no memory ordering and visibility guarantees provided for the memory accesses performed prior to cluster.arrive.

[For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-barrier-cluster)

Attributes: ¶

nvvm.cluster.wait (NVVM::ClusterWaitOp) ¶

Cluster Barrier Wait Op

Syntax:

operation ::= `nvvm.cluster.wait` attr-dict

The cluster.wait causes the executing thread to wait for all non-exited threads of the cluster to perform cluster.arrive. The aligned attribute, when provided, generates the .aligned version of the PTX instruction.

[For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-barrier-cluster)

Attributes: ¶

nvvm.cp.async.bulk.commit.group (NVVM::CpAsyncBulkCommitGroupOp) ¶

Syntax:

operation ::= `nvvm.cp.async.bulk.commit.group` attr-dict

This Op commits all prior initiated but uncommitted cp.async.bulk instructions into a cp.async.bulk-group.

[For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#data-movement-and-conversion-instructions-cp-async-bulk-commit-group)

nvvm.cp.async.bulk.tensor.global.shared.cta (NVVM::CpAsyncBulkTensorSharedCTAToGlobalOp) ¶

Syntax:

operation ::= `nvvm.cp.async.bulk.tensor.global.shared.cta` $tmaDescriptor `,`
              $srcMem `,`
              `box` `[`$coordinates `]`
              (`,` `predicate` `=` $predicate^)?
              attr-dict  `:` type(operands)

Traits: AttrSizedOperandSegments

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.cp.async.bulk.tensor.shared.cluster.global (NVVM::CpAsyncBulkTensorGlobalToSharedClusterOp) ¶

Syntax:

operation ::= `nvvm.cp.async.bulk.tensor.shared.cluster.global` $dstMem `,`
              $tmaDescriptor `,`
              $mbar `,`
              `box` `[`$coordinates `]`
              (`im2col` `[` $im2colOffsets^ `]` )?
              (`multicast_mask` `=` $multicastMask^ )?
              (`l2_cache_hint` `=` $l2CacheHint^ )?
              (`predicate` `=` $predicate^)?
              attr-dict  `:` type($dstMem) `,` type($tmaDescriptor)

Initiates an asynchronous copy operation on the tensor data from global memory to shared memory.

The Op operates has two load modes:

1. Tiled Mode: It’s the default mode. The source multi-dimensional tensor layout is preserved at the destination.

2. Im2col Mode: This mode is used when im2colOffsets operands are present. the elements in the Bounding Box of the source tensor are rearranged into columns at the destination. In this mode, the tensor has to be at least 3-dimensional.

The multicastMask operand is optional. When it is present, the Op copies data from global memory to shared memory of multiple CTAs in the cluster. Operand multicastMask specifies the destination CTAs in the cluster such that each bit position in the 16-bit multicastMask operand corresponds to the nvvm.read.ptx.sreg.ctaid of the destination CTA.

The l2CacheHint operand is optional, and it is used to specify cache eviction policy that may be used during the memory access.

[For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#data-movement-and-conversion-instructions-cp-async-bulk-tensor)

Traits: AttrSizedOperandSegments

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.cp.async.bulk.wait_group (NVVM::CpAsyncBulkWaitGroupOp) ¶

Syntax:

operation ::= `nvvm.cp.async.bulk.wait_group` $group attr-dict

Op waits for completion of the most recent bulk async-groups.

The $group operand tells waiting has to be done until for $group or fewer of the most recent bulk async-groups. If $group is 0, the op wait until all the most recent bulk async-groups have completed.

The $read indicates that the waiting has to be done until all the bulk async operations in the specified bulk async-group have completed reading from their source locations.

[For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#data-movement-and-conversion-instructions-cp-async-bulk-wait-group)

Attributes: ¶

nvvm.cp.async.commit.group (NVVM::CpAsyncCommitGroupOp) ¶

Syntax:

operation ::= `nvvm.cp.async.commit.group` attr-dict

nvvm.cp.async.mbarrier.arrive (NVVM::CpAsyncMBarrierArriveOp) ¶

NVVM Dialect Op for cp.async.mbarrier.arrive

Syntax:

operation ::= `nvvm.cp.async.mbarrier.arrive` $addr attr-dict `:` type(operands)

The cp.async.mbarrier.arrive Op makes the mbarrier object track all prior cp.async operations initiated by the executing thread. The addr operand specifies the address of the mbarrier object in generic address space. The noinc attr impacts how the mbarrier’s state is updated. [For more information, refer PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-cp-async-mbarrier-arrive)

Attributes: ¶

Operands: ¶

nvvm.cp.async.mbarrier.arrive.shared (NVVM::CpAsyncMBarrierArriveSharedOp) ¶

NVVM Dialect Op for cp.async.mbarrier.arrive.shared

Syntax:

operation ::= `nvvm.cp.async.mbarrier.arrive.shared` $addr attr-dict `:` type(operands)

The cp.async.mbarrier.arrive.shared Op makes the mbarrier object track all prior cp.async operations initiated by the executing thread. The addr operand specifies the address of the mbarrier object in shared memory. The noinc attr impacts how the mbarrier’s state is updated. [For more information, refer PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-cp-async-mbarrier-arrive)

Attributes: ¶

Operands: ¶

nvvm.cp.async.shared.global (NVVM::CpAsyncOp) ¶

Syntax:

operation ::= `nvvm.cp.async.shared.global` $dst `,` $src `,` $size `,` `cache` `=` $modifier (`,` $cpSize^)? attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Attributes: ¶

Enum attribute of the different kinds of cache operators for load instructions.

For more information, see PTX ISA 

Operands: ¶

nvvm.cp.async.wait.group (NVVM::CpAsyncWaitGroupOp) ¶

Syntax:

operation ::= `nvvm.cp.async.wait.group` $n attr-dict

Attributes: ¶

nvvm.elect.sync (NVVM::ElectSyncOp) ¶

Syntax:

operation ::= `nvvm.elect.sync` attr-dict `->` type(results)

Interfaces: BasicPtxBuilderInterface

Results: ¶

nvvm.fence.mbarrier.init (NVVM::FenceMbarrierInitOp) ¶

Syntax:

operation ::= `nvvm.fence.mbarrier.init` attr-dict

Fence operation that applies on the prior nvvm.mbarrier.init [For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-membar)

Interfaces: BasicPtxBuilderInterface

nvvm.fence.proxy (NVVM::FenceProxyOp) ¶

Syntax:

operation ::= `nvvm.fence.proxy` attr-dict

Fence operation with proxy to establish an ordering between memory accesses that may happen through different proxies. [For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#parallel-synchronization-and-communication-instructions-membar)

Interfaces: BasicPtxBuilderInterface

Attributes: ¶

nvvm.fence.sc.cluster (NVVM::FenceScClusterOp) ¶

Syntax:

operation ::= `nvvm.fence.sc.cluster` attr-dict

nvvm.ldmatrix (NVVM::LdMatrixOp) ¶

Cooperative matrix load

Syntax:

operation ::= `nvvm.ldmatrix` $ptr attr-dict `:` functional-type($ptr, $res)

Attributes: ¶

Operands: ¶

Results: ¶

nvvm.mbarrier.arrive (NVVM::MBarrierArriveOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.arrive` $addr attr-dict `:` type($addr) `->` type($res)

Operands: ¶

Results: ¶

nvvm.mbarrier.arrive.expect_tx (NVVM::MBarrierArriveExpectTxOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.arrive.expect_tx` $addr `,` $txcount (`,` `predicate` `=` $predicate^)? attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.mbarrier.arrive.expect_tx.shared (NVVM::MBarrierArriveExpectTxSharedOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.arrive.expect_tx.shared` $addr `,` $txcount (`,` `predicate` `=` $predicate^)? attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.mbarrier.arrive.nocomplete (NVVM::MBarrierArriveNocompleteOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.arrive.nocomplete` $addr `,` $count attr-dict `:` type(operands) `->` type($res)

Operands: ¶

Results: ¶

nvvm.mbarrier.arrive.nocomplete.shared (NVVM::MBarrierArriveNocompleteSharedOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.arrive.nocomplete.shared` $addr `,` $count attr-dict `:` type(operands) `->` type($res)

Operands: ¶

Results: ¶

nvvm.mbarrier.arrive.shared (NVVM::MBarrierArriveSharedOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.arrive.shared` $addr attr-dict `:` qualified(type($addr)) `->` type($res)

Operands: ¶

Results: ¶

nvvm.mbarrier.init (NVVM::MBarrierInitOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.init` $addr `,` $count (`,` `predicate` `=` $predicate^)? attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.mbarrier.init.shared (NVVM::MBarrierInitSharedOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.init.shared` $addr `,` $count (`,` `predicate` `=` $predicate^)? attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.mbarrier.inval (NVVM::MBarrierInvalOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.inval` $addr attr-dict `:` type(operands)

Operands: ¶

nvvm.mbarrier.inval.shared (NVVM::MBarrierInvalSharedOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.inval.shared` $addr attr-dict `:` type(operands)

Operands: ¶

nvvm.mbarrier.test.wait (NVVM::MBarrierTestWaitOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.test.wait` $addr `,` $state attr-dict `:` type(operands) `->` type($res)

Operands: ¶

Results: ¶

nvvm.mbarrier.test.wait.shared (NVVM::MBarrierTestWaitSharedOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.test.wait.shared` $addr `,` $state attr-dict `:` type(operands) `->` type($res)

Operands: ¶

Results: ¶

nvvm.mbarrier.try_wait.parity (NVVM::MBarrierTryWaitParityOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.try_wait.parity` $addr `,` $phase `,` $ticks attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.mbarrier.try_wait.parity.shared (NVVM::MBarrierTryWaitParitySharedOp) ¶

Syntax:

operation ::= `nvvm.mbarrier.try_wait.parity.shared` $addr `,` $phase `,` $ticks attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.mma.sync (NVVM::MmaOp) ¶

Cooperative matrix-multiply and accumulate

The nvvm.mma.sync operation collectively performs the operation D = matmul(A, B) + C using all threads in a warp.

All the threads in the warp must execute the same mma.sync operation.

For each possible multiplicand PTX data type, there are one or more possible instruction shapes given as “mMnNkK”. The below table describes the posssibilities as well as the types required for the operands. Note that the data type for C (the accumulator) and D (the result) can vary independently when there are multiple possibilities in the “C/D Type” column.

When an optional attribute cannot be immediately inferred from the types of the operands and the result during parsing or validation, an error will be raised.

b1Op is only relevant when the binary (b1) type is given to multiplicandDataType. It specifies how the multiply-and-acumulate is performed and is either xor_popc or and_poc. The default is xor_popc.

intOverflowBehavior is only relevant when the multiplicandType attribute is one of u8, s8, u4, s4, this attribute describes how overflow is handled in the accumulator. When the attribute is satfinite, the accumulator values are clamped in the int32 range on overflow. This is the default behavior. Alternatively, accumulator behavior wrapped can also be specified, in which case overflow wraps from one end of the range to the other.

layoutA and layoutB are required and should generally be set to #nvvm.mma_layout<row> and #nvvm.mma_layout<col> respectively, but other combinations are possible for certain layouts according to the table below.

| A/B Type | Shape     | ALayout | BLayout | A Type   | B Type   | C/D Type          |
|----------|-----------|---------|---------|----------|----------|-------------------|
| f64      | .m8n8k4   | row     | col     | 1x f64   | 1x f64   | 2x f64            |
| f16      | .m8n8k4   | row/col | row/col | 2x f16x2 | 2x f16x2 | 4x f16x2 or 8xf32 |
|          | .m16n8k8  | row     | col     | 2x f16x2 | 1x f16x2 | 2x f16x2 or 4 f32 |
|          | .m16n8k16 | row     | col     | 4x f16x2 | 2x f16x2 | 2x f16x2 or 4 f32 |
| bf16     | .m16n8k8  | row     | col     | 2x f16x2 | 1x f16x2 | 2x f16x2 or 4 f32 |
|          | .m16n8k16 | row     | col     | 4x f16x2 | 2x f16x2 | 2x f16x2 or 4 f32 |
| tf32     | .m16n8k4  | row     | col     | 2x i32   | 1x i32   | 4x f32            |
|          | .m16n8k8  | row     | col     | 4x i32   | 2x i32   | 2x f16x2 or 4 f32 |
| u8/s8    | .m8n8k16  | row     | col     | 1x i32   | 1x i32   | 2x i32            |
|          | .m16n8k16 | row     | col     | 2x i32   | 1x i32   | 4x i32            |
|          | .m16n8k32 | row     | col     | 4x i32   | 2x i32   | 4x i32            |
| u4/s4    | .m8n8k32  | row     | col     | 1x i32   | 1x i32   | 2x i32            |
|          | m16n8k32  | row     | col     | 2x i32   | 1x i32   | 4x i32            |
|          | m16n8k64  | row     | col     | 4x i32   | 2x i32   | 4x i32            |
| b1       | m8n8k128  | row     | col     | 1x i32   | 1x i32   | 2x i32            |
|          | m16n8k128 | row     | col     | 2x i32   | 1x i32   | 4x i32            |

Example:

%128 = nvvm.mma.sync A[%120, %121, %122, %123]
                     B[%124, %125]
                     C[%126, %127]
                     {layoutA = #nvvm.mma_layout<row>,
                      layoutB = #nvvm.mma_layout<col>,
                      shape = {k = 16 : i32, m = 16 : i32, n = 8 : i32}}
    : (vector<2xf16>, vector<2xf16>, vector<2xf16>)
       -> !llvm.struct<(vector<2xf16>, vector<2xf16>)>

Traits: AttrSizedOperandSegments

Attributes: ¶

Operands: ¶

Results: ¶

nvvm.prefetch.tensormap (NVVM::PrefetchTensorMapOp) ¶

Syntax:

operation ::= `nvvm.prefetch.tensormap` $tmaDescriptor (`,` `predicate` `=` $predicate^)? attr-dict `:` type(operands)

Interfaces: BasicPtxBuilderInterface

Operands: ¶

nvvm.rcp.approx.ftz.f (NVVM::RcpApproxFtzF32Op) ¶

Syntax:

operation ::= `nvvm.rcp.approx.ftz.f` $arg attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Operands: ¶

Results: ¶

nvvm.read.ptx.sreg.clock (NVVM::ClockOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.clock` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.clock64 (NVVM::Clock64Op) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.clock64` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.ctaid.x (NVVM::BlockInClusterIdXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.ctaid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.ctaid.y (NVVM::BlockInClusterIdYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.ctaid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.ctaid.z (NVVM::BlockInClusterIdZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.ctaid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.ctarank (NVVM::ClusterId) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.ctarank` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.nctaid.x (NVVM::GridInClusterDimXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.nctaid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.nctaid.y (NVVM::GridInClusterDimYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.nctaid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.nctaid.z (NVVM::GridInClusterDimZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.nctaid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.cluster.nctarank (NVVM::ClusterDim) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.cluster.nctarank` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.clusterid.x (NVVM::ClusterIdXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.clusterid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.clusterid.y (NVVM::ClusterIdYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.clusterid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.clusterid.z (NVVM::ClusterIdZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.clusterid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.ctaid.x (NVVM::BlockIdXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.ctaid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.ctaid.y (NVVM::BlockIdYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.ctaid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.ctaid.z (NVVM::BlockIdZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.ctaid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.laneid (NVVM::LaneIdOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.laneid` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.nclusterid.x (NVVM::ClusterDimXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.nclusterid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.nclusterid.y (NVVM::ClusterDimYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.nclusterid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.nclusterid.z (NVVM::ClusterDimZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.nclusterid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.nctaid.x (NVVM::GridDimXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.nctaid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.nctaid.y (NVVM::GridDimYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.nctaid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.nctaid.z (NVVM::GridDimZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.nctaid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.ntid.x (NVVM::BlockDimXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.ntid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.ntid.y (NVVM::BlockDimYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.ntid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.ntid.z (NVVM::BlockDimZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.ntid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.tid.x (NVVM::ThreadIdXOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.tid.x` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.tid.y (NVVM::ThreadIdYOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.tid.y` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.tid.z (NVVM::ThreadIdZOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.tid.z` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.read.ptx.sreg.warpsize (NVVM::WarpSizeOp) ¶

Syntax:

operation ::= `nvvm.read.ptx.sreg.warpsize` attr-dict `:` type($res)

Traits: AlwaysSpeculatableImplTrait

Interfaces: ConditionallySpeculatable, NoMemoryEffect (MemoryEffectOpInterface)

Effects: MemoryEffects::Effect{}

Results: ¶

nvvm.redux.sync (NVVM::ReduxOp) ¶

Syntax:

operation ::= `nvvm.redux.sync` $kind $val `,` $mask_and_clamp  attr-dict `:` type($val) `->` type($res)

Attributes: ¶

Operands: ¶

Results: ¶

nvvm.setmaxregister (NVVM::SetMaxRegisterOp) ¶

Syntax:

operation ::= `nvvm.setmaxregister` $action $regCount attr-dict

Attributes: ¶

nvvm.shfl.sync (NVVM::ShflOp) ¶

NVVM Dialect Op for shfl.sync

Syntax:

operation ::= `nvvm.shfl.sync` $kind $thread_mask `,` $val `,` $offset `,` $mask_and_clamp  attr-dict
              `:` type($val) `->` type($res)

The shfl.sync Op implements data shuffle within threads of a warp. The thread_mask denotes the threads participating in the Op where the bit position corresponds to a particular thread’s laneid. The offset specifies a source lane or source lane offset (depending on kind). The val is the input value to be copied from the source. The mask_and_clamp contains two packed values specifying a mask for logically splitting warps into sub-segments and an upper bound for clamping the source lane index. [For more information, refer PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/#data-movement-and-conversion-instructions-shfl-sync)

Attributes: ¶

Operands: ¶

Results: ¶

nvvm.stmatrix (NVVM::StMatrixOp) ¶

Cooperative matrix store

Syntax:

operation ::= `nvvm.stmatrix` $ptr `,` $sources attr-dict `:` type(operands)

Collectively store one or more matrices across all threads in a warp to the location indicated by the address operand $ptr in shared memory. [For more information, see PTX ISA] ( https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#warp-level-matrix-store-instruction-stmatrix)

Interfaces: BasicPtxBuilderInterface

Attributes: ¶

Operands: ¶

nvvm.vote.ballot.sync (NVVM::VoteBallotOp) ¶

Operands: ¶

Results: ¶

nvvm.wgmma.commit.group.sync.aligned (NVVM::WgmmaGroupSyncAlignedOp) ¶

Syntax:

operation ::= `nvvm.wgmma.commit.group.sync.aligned` attr-dict

Commits all prior uncommitted warpgroup level matrix multiplication operations.

For more information, see PTX ISA

Interfaces: BasicPtxBuilderInterface

nvvm.wgmma.fence.aligned (NVVM::WgmmaFenceAlignedOp) ¶

Syntax:

operation ::= `nvvm.wgmma.fence.aligned` attr-dict

Enforce an ordering of register accesses between warpgroup level matrix multiplication and other operations.

For more information, see PTX ISA

Interfaces: BasicPtxBuilderInterface

nvvm.wgmma.mma_async (NVVM::WgmmaMmaAsyncOp) ¶

Syntax:

operation ::= `nvvm.wgmma.mma_async` $descriptorA `,` $descriptorB `,` $inouts `,` $shape `,`
              `D` `[` $typeD `,` $scaleD (`,` $satfinite^)? `]` `,`
              `A` `[` $typeA `,` $scaleA `,` $layoutA `]` `,`
              `B` `[` $typeB `,` $scaleB `,` $layoutB `]`
              attr-dict `:`
              type($inouts) `->` type($results)

The warpgroup (128 threads) level matrix multiply and accumulate operation has either of the following forms, where matrix D is called accumulator: D = A * B + D D = A * B, where the input from accumulator D is disabled.

Supported shapes:

|--------------|--------------|------------|--------------|---------------|
|              |              |            |              |f16+=e4m3*e4m3 |
|              |              |            |              |f16+=e5m2*e5m2 |
|f32+=tf32*tf32|f16+=f16 *f16 | s32+=s8*s8 |s32 += b1 * b1|f16+=e5m2*e4m3 |
|              |f32+=f16 *f16 | s32+=u8*u8 |              |f16+=e4m3*e5m2 |
|              |f32+=bf16*bf16| s32+=u8*u8 |              |f16+=e4m3*e5m2 |
|              |f32+=bf16*bf16| s32+=s8*u8 |              |f32+=e4m3*e4m3 |
|              |              | s32+=u8*s8 |              |f32+=e5m2*e5m2 |
|              |              |            |              |f32+=e4m3*e5m2 |
|              |              |            |              |f32+=e4m3*e5m2 |
|--------------|--------------|------------|--------------|---------------|
|   .m64n8k8   |  .m64n8k16   | .m64n8k32  | .m64n8k256   | .m64n8k32     |
|   .m64n16k8  |  .m64n16k16  | .m64n16k32 | .m64n16k256  | .m64n16k32    |
|   .m64n24k8  |  .m64n24k16  | .m64n24k32 | .m64n24k256  | .m64n24k32    |
|   .m64n32k8  |  .m64n32k16  | .m64n32k32 | .m64n32k256  | .m64n32k32    |
|   .m64n40k8  |  .m64n40k16  | .m64n48k32 | .m64n48k256  | .m64n40k32    |
|   .m64n48k8  |  .m64n48k16  | .m64n64k32 | .m64n64k256  | .m64n48k32    |
|   .m64n56k8  |  .m64n56k16  | .m64n80k32 | .m64n80k256  | .m64n56k32    |
|   .m64n64k8  |  .m64n64k16  | .m64n96k32 | .m64n96k256  | .m64n64k32    |
|   .m64n72k8  |  .m64n72k16  | .m64n112k32| .m64n112k256 | .m64n72k32    |
|   .m64n80k8  |  .m64n80k16  | .m64n128k32| .m64n128k256 | .m64n80k32    |
|   .m64n88k8  |  .m64n88k16  | .m64n144k32| .m64n144k256 | .m64n88k32    |
|   .m64n96k8  |  .m64n96k16  | .m64n160k32| .m64n160k256 | .m64n96k32    |
|   .m64n104k8 |  .m64n104k16 | .m64n176k32| .m64n176k256 | .m64n104k32   |
|   .m64n112k8 |  .m64n112k16 | .m64n192k32| .m64n192k256 | .m64n112k32   |
|   .m64n120k8 |  .m64n120k16 | .m64n208k32| .m64n208k256 | .m64n120k32   |
|   .m64n128k8 |  .m64n128k16 | .m64n224k32| .m64n224k256 | .m64n128k32   |
|   .m64n136k8 |  .m64n136k16 | .m64n240k32| .m64n240k256 | .m64n136k32   |
|   .m64n144k8 |  .m64n144k16 | .m64n256k32| .m64n256k256 | .m64n144k32   |
|   .m64n152k8 |  .m64n152k16 |            |              | .m64n152k32   |
|   .m64n160k8 |  .m64n160k16 |            |              | .m64n160k32   |
|   .m64n168k8 |  .m64n168k16 |            |              | .m64n168k32   |
|   .m64n176k8 |  .m64n176k16 |            |              | .m64n176k32   |
|   .m64n184k8 |  .m64n184k16 |            |              | .m64n184k32   |
|   .m64n192k8 |  .m64n192k16 |            |              | .m64n192k32   |
|   .m64n200k8 |  .m64n200k16 |            |              | .m64n200k32   |
|   .m64n208k8 |  .m64n208k16 |            |              | .m64n208k32   |
|   .m64n216k8 |  .m64n216k16 |            |              | .m64n216k32   |
|   .m64n224k8 |  .m64n224k16 |            |              | .m64n224k32   |
|   .m64n232k8 |  .m64n232k16 |            |              | .m64n232k32   |
|   .m64n240k8 |  .m64n240k16 |            |              | .m64n240k32   |
|   .m64n248k8 |  .m64n248k16 |            |              | .m64n248k32   |
|   .m64n256k8 |  .m64n256k16 |            |              | .m64n256k32   |
|--------------|--------------|------------|--------------|---------------|

For more information, see PTX ISA

Interfaces: BasicPtxBuilderInterface

Attributes: ¶

Operands: ¶

Results: ¶

nvvm.wgmma.wait.group.sync.aligned (NVVM::WgmmaWaitGroupSyncOp) ¶

Syntax:

operation ::= `nvvm.wgmma.wait.group.sync.aligned` attr-dict $group

Signal the completion of a preceding warpgroup operation.

For more information, see PTX ISA

Interfaces: BasicPtxBuilderInterface

Attributes: ¶

nvvm.wmma.load (NVVM::WMMALoadOp) ¶

Warp synchronous matrix load

Syntax:

operation ::= `nvvm.wmma.load` $ptr `,` $stride attr-dict `:` functional-type($ptr, $res)

Attributes: ¶

Operands: ¶

Results: ¶

nvvm.wmma.mma (NVVM::WMMAMmaOp) ¶

Warp synchronous matrix-multiply accumulate using tensor cores.

Syntax:

operation ::= `nvvm.wmma.mma` $args attr-dict `:` functional-type($args, $res)

Attributes: ¶

Operands: ¶

Results: ¶

nvvm.wmma.store (NVVM::WMMAStoreOp) ¶

Warp synchronous matrix store

Syntax:

operation ::= `nvvm.wmma.store` $ptr `,` $stride `,` $args attr-dict `:` qualified(type($ptr)) `,`
              type($args)

Attributes: ¶

Operands: ¶

Attributes ¶

LoadCacheModifierKindAttr ¶

NVVM load cache modifier kind

Syntax:

#nvvm.load_cache_modifier<
  ::mlir::NVVM::LoadCacheModifierKind   # value
>

Enum attribute of the different kinds of cache operators for load instructions.

For more information, see PTX ISA

Parameters: ¶

MMAB1OpAttr ¶

MMA binary operations

Syntax:

#nvvm.mma_b1op<
  ::mlir::NVVM::MMAB1Op   # value
>

Enum cases:

• none (none)
• xor_popc (xor_popc)
• and_popc (and_popc)

Parameters: ¶

MMAFragAttr ¶

NVVM MMA frag type

Syntax:

#nvvm.mma_frag<
  ::mlir::NVVM::MMAFrag   # value
>

Enum cases:

• a (a)
• b (b)
• c (c)

Parameters: ¶

MMAIntOverflowAttr ¶

MMA overflow options

Syntax:

#nvvm.mma_int_overflow<
  ::mlir::NVVM::MMAIntOverflow   # value
>

Enum cases:

• satfinite (satfinite)
• wrapped (wrapped)

Parameters: ¶

MMALayoutAttr ¶

NVVM MMA layout

Syntax:

#nvvm.mma_layout<
  ::mlir::NVVM::MMALayout   # value
>

Enum cases:

• row (row)
• col (col)

Parameters: ¶

MMATypesAttr ¶

NVVM MMA types

Syntax:

#nvvm.mma_type<
  ::mlir::NVVM::MMATypes   # value
>

Enum cases:

• f16 (f16)
• f32 (f32)
• tf32 (tf32)
• bf16 (bf16)
• s8 (s8)
• u8 (u8)
• s32 (s32)
• s4 (s4)
• u4 (u4)
• b1 (b1)
• f64 (f64)

Parameters: ¶

MMAShapeAttr ¶

Attribute for MMA operation shape.

Syntax:

#nvvm.shape<
  int,   # m
  int,   # n
  int   # k
>

Parameters: ¶

NVVMTargetAttr ¶

Syntax:

#nvvm.target<
  int,   # O
  ::llvm::StringRef,   # triple
  ::llvm::StringRef,   # chip
  ::llvm::StringRef,   # features
  DictionaryAttr,   # flags
  ArrayAttr   # link
>

GPU target attribute for controlling compilation of NVIDIA targets. All parameters decay into default values if not present.

Examples:

1. Target with default values.

  gpu.module @mymodule [#nvvm.target] attributes {...} {
    ...
  }

2. Target with sm_90 chip and fast math.

  gpu.module @mymodule [#nvvm.target<chip = "sm_90", flags = {fast}>] {
    ...
  }

Parameters: ¶

ProxyKindAttr ¶

Proxy kind

Syntax:

#nvvm.proxy_kind<
  ::mlir::NVVM::ProxyKind   # value
>

Enum cases:

• alias (alias)
• async (async)
• async.global (async_global)
• async.shared (async_shared)

Parameters: ¶

ReduxKindAttr ¶

NVVM redux kind

Syntax:

#nvvm.redux_kind<
  ::mlir::NVVM::ReduxKind   # value
>

Enum cases:

• add (ADD)
• and (AND)
• max (MAX)
• min (MIN)
• or (OR)
• umax (UMAX)
• umin (UMIN)
• xor (XOR)

Parameters: ¶

SetMaxRegisterActionAttr ¶

NVVM set max register action

Syntax:

#nvvm.action<
  ::mlir::NVVM::SetMaxRegisterAction   # value
>

Enum cases:

• decrease (decrease)
• increase (increase)

Parameters: ¶

SharedSpaceAttr ¶

Shared memory space

Syntax:

#nvvm.shared_space<
  ::mlir::NVVM::SharedSpace   # value
>

Enum cases:

• cta (shared_cta)
• cluster (shared_cluster)

Parameters: ¶

ShflKindAttr ¶

NVVM shuffle kind

Syntax:

#nvvm.shfl_kind<
  ::mlir::NVVM::ShflKind   # value
>

Enum cases:

• bfly (bfly)
• up (up)
• down (down)
• idx (idx)

Parameters: ¶

WGMMAScaleInAttr ¶

WGMMA overflow options

Syntax:

#nvvm.wgmma_scale_in<
  ::mlir::NVVM::WGMMAScaleIn   # value
>

Enum cases:

• one (one)
• neg (neg)

Parameters: ¶

WGMMAScaleOutAttr ¶

WGMMA input predicate

Syntax:

#nvvm.wgmma_scale_out<
  ::mlir::NVVM::WGMMAScaleOut   # value
>

Enum cases:

• zero (zero)
• one (one)

Parameters: ¶

WGMMATypesAttr ¶

NVVM WGMMA types

Syntax:

#nvvm.wgmma_type<
  ::mlir::NVVM::WGMMATypes   # value
>

Enum cases:

• f16 (f16)
• tf32 (tf32)
• u8 (u8)
• s8 (s8)
• b1 (b1)
• bf16 (bf16)
• e4m3 (e4m3)
• e5m2 (e5m2)
• f32 (f32)
• s32 (s32)

Parameters: ¶