[NVPTX] Add im2colw/w128 modes support to TMA intrinsics

This patch adds support for the following modes in
the TMA intrinsics:

* TMA G2S Copy: im2col_w, im2col_w_128 and tile_gather4_2d.
* TMA Prefetch: im2col_w, im2col_w_128 and tile_gather4_2d.
* TMA S2G Copy: tile_scatter4_2d mode
* TMA G2S-CTA copy: tile, im2col, im2col_w, im2col_w_128 and
                    tile_gather4_2d.

Signed-off-by: Durgadoss R <[email protected]>

Author: durga4github

llvm/docs/NVPTXUsage.rst

@@ -1072,6 +1072,8 @@ Syntax:
   declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.tile.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
   declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.tile.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
 
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.tile.gather4.2d(ptr addrspace(7) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %x0, i32 %y0, i32 %y1, i32 %y2, i32 %y3, i16 %mc, i64 %ch, i1 %flag_mc, i1 %flag_ch, i32 %flag_cta_group)
+
 Overview:
 """""""""
 
@@ -1082,7 +1084,13 @@ global memory to shared::cluster memory (indicated by the ``g2s`` prefix)
 in ``tile`` mode. In tile mode, the multi-dimensional layout of the
 source tensor is preserved at the destination. The dimension of the
 tensor data ranges from 1d to 5d with the coordinates specified
-by the ``i32 %d0 ... i32 %d4`` arguments.
+by the ``i32 %d0 ... i32 %d4`` arguments. In ``tile.gather4`` mode,
+four rows in a 2D tensor are combined to form a single 2D destination
+tensor. The first coordinate ``i32 %x0`` denotes the column index
+followed by four coordinates indicating the four row-indices.
+So, this mode takes a total of 5 coordinates as input arguments.
+For more information on ``gather4`` mode, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/#tensor-tiled-scatter4-gather4-modes>`_.
 
 * The last three arguments to these intrinsics are flags
   indicating support for multicast, cache_hint and cta_group::1/2
@@ -1116,10 +1124,18 @@ Syntax:
 
 .. code-block:: llvm
 
-  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.3d(ptr addrspace(3) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %im2col0, i16 %mc, i64 %ch, i1 %flag_mc, i1 %flag_ch, i32 %flag_cta_group)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.3d(ptr addrspace(7) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %im2col0, i16 %mc, i64 %ch, i1 %flag_mc, i1 %flag_ch, i32 %flag_cta_group)
   declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i16 %im2col0, i16 %im2col1, ...)
   declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, i16 %im2col0, i16 %im2col1, i16 %im2col2, ...)
 
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.w.3d(ptr addrspace(7) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %wHalo, i16 %wOffset, i16 %mc, i64 %ch, i1 %flag_mc, i1 %flag_ch, i32 %flag_cta_group)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.w.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.w.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
+
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.w.128.3d(ptr addrspace(7) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %wHalo, i16 %wOffset, i16 %mc, i64 %ch, i1 %flag_mc, i1 %flag_ch, i32 %flag_cta_group)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.w.128.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.im2col.w.128.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
+
 Overview:
 """""""""
 
@@ -1131,10 +1147,105 @@ in ``im2col`` mode. In im2col mode, some dimensions of the source tensor
 are unrolled into a single dimensional column at the destination. In this
 mode, the tensor has to be at least three-dimensional. Along with the tensor
 coordinates, im2col offsets are also specified (denoted by
-``i16 im2col0...i16 %im2col2``). The number of im2col offsets is two less
-than the number of dimensions of the tensor operation. The last three arguments
-to these intrinsics are flags, with the same functionality as described
-in the ``tile`` mode intrinsics above.
+``i16 im2col0...i16 %im2col2``). For the ``im2col`` mode, the number of offsets
+is two less than the number of dimensions of the tensor operation. For the
+``im2col.w`` and ``im2col.w.128`` mode, the number of offsets is always 2,
+denoted by ``i16 %wHalo`` and ``i16 %wOffset`` arguments. For more information
+on ``im2col.w`` and ``im2col.w.128`` modes, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/#tensor-im2col-w-w128-modes>`_.
+
+The last three arguments to these intrinsics are flags, with the same functionality
+as described in the ``tile`` mode intrinsics above.
+
+For more information, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#data-movement-and-conversion-instructions-cp-async-bulk-tensor>`_.
+
+'``llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.[1-5]d``'
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Syntax:
+"""""""
+
+.. code-block:: llvm
+
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.1d(ptr addrspace(3) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i64 %ch, i1 %flag_ch)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.2d(..., i32 %d0, i32 %d1, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.3d(..., i32 %d0, i32 %d1, i32 %d2, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
+
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.gather4.2d(ptr addrspace(3) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %x0, i32 %y0, i32 %y1, i32 %y2, i32 %y3, i64 %ch, i1 %flag_ch)
+
+Overview:
+"""""""""
+
+The '``@llvm.nvvm.cp.async.bulk.tensor.g2s.cta.tile.[1-5]d``' intrinsics
+correspond to the ``cp.async.bulk.tensor.[1-5]d.shared::cta.global.*``
+set of PTX instructions. These instructions initiate an asynchronous
+copy of tensor data from global memory to shared::cta memory in
+``tile`` mode. In tile mode, the multi-dimensional layout of the
+source tensor is preserved at the destination. The dimension of the
+tensor data ranges from 1d to 5d with the coordinates specified
+by the ``i32 %d0 ... i32 %d4`` arguments. In ``tile.gather4`` mode,
+four rows in a 2D tensor are combined to form a single 2D destination
+tensor. The first coordinate ``i32 %x0`` denotes the column index
+followed by four coordinates indicating the four row-indices.
+So, this mode takes a total of 5 coordinates as input arguments.
+For more information on ``gather4`` mode, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/#tensor-tiled-scatter4-gather4-modes>`_.
+
+* The last argument to these intrinsics is a boolean flag
+  indicating support for cache_hint. This flag argument must
+  be a compile-time constant. When set, it indicates a valid
+  cache_hint (``i64 %ch``) and generates the ``.L2::cache_hint``
+  variant of the PTX instruction.
+
+For more information, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#data-movement-and-conversion-instructions-cp-async-bulk-tensor>`_.
+
+'``llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.[3-5]d``'
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Syntax:
+"""""""
+
+.. code-block:: llvm
+
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.3d(ptr addrspace(3) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %im2col0, i64 %ch, i1 %flag_ch)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i16 %im2col0, i16 %im2col1, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, i16 %im2col0, i16 %im2col1, i16 %im2col2, ...)
+
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.w.3d(ptr addrspace(3) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %wHalo, i16 %wOffset, i64 %ch, i1 %flag_ch)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.w.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.w.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
+
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.w.128.3d(ptr addrspace(3) %dst, ptr addrspace(3) %bar, ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %wHalo, i16 %wOffset, i64 %ch, i1 %flag_ch)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.w.128.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.w.128.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
+
+Overview:
+"""""""""
+
+The '``@llvm.nvvm.cp.async.bulk.tensor.g2s.cta.im2col.[3-5]d``' intrinsics
+correspond to the ``cp.async.bulk.tensor.[1-5]d.shared::cta.global.*``
+set of PTX instructions. These instructions initiate an asynchronous copy
+of tensor data from global memory to shared::cta memory in ``im2col`` mode.
+In im2col mode, some dimensions of the source tensor are unrolled into a
+single dimensional column at the destination. In this mode, the tensor has
+to be at least three-dimensional. Along with the tensor coordinates, im2col
+offsets are also specified (denoted by ``i16 im2col0...i16 %im2col2``).
+For the ``im2col`` mode, the number of offsets is two less than the number
+of dimensions of the tensor operation. For the ``im2col.w`` and ``im2col.w.128``
+mode, the number of offsets is always 2, denoted by ``i16 %wHalo`` and
+``i16 %wOffset`` arguments. For more information on ``im2col.w`` and
+``im2col.w.128`` modes, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/#tensor-im2col-w-w128-modes>`_.
+
+* The last argument to these intrinsics is a boolean flag
+  indicating support for cache_hint. This flag argument must
+  be a compile-time constant. When set, it indicates a valid
+  cache_hint (``i64 %ch``) and generates the ``.L2::cache_hint``
+  variant of the PTX instruction.
 
 For more information, refer PTX ISA
 `<https://docs.nvidia.com/cuda/parallel-thread-execution/index.html#data-movement-and-conversion-instructions-cp-async-bulk-tensor>`_.
@@ -1153,6 +1264,8 @@ Syntax:
   declare void @llvm.nvvm.cp.async.bulk.tensor.s2g.tile.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
   declare void @llvm.nvvm.cp.async.bulk.tensor.s2g.tile.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
 
+  declare void @llvm.nvvm.cp.async.bulk.tensor.s2g.tile.scatter4.2d(ptr addrspace(3) %src, ptr %tensor_map, i32 %x0, i32 %y0, i32 %y1, i32 %y2, i32 %y3, i64 %ch, i1 %flag_ch)
+
 Overview:
 """""""""
 
@@ -1162,6 +1275,12 @@ These instructions initiate an asynchronous copy of tensor data from
 shared::cta to global memory (indicated by the ``s2g`` prefix)
 in ``tile`` mode. The dimension of the tensor data ranges from 1d to 5d
 with the coordinates specified by the ``i32 %d0 ... i32 %d4`` arguments.
+In ``tile.scatter4`` mode, a single 2D source tensor is divided into
+four rows in the 2D destination tensor. The first coordinate ``i32 %x0``
+denotes the column index followed by four coordinates indicating the
+four row-indices. So, this mode takes a total of 5 coordinates as input arguments.
+For more information on ``scatter4`` mode, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/#tensor-tiled-scatter4-gather4-modes>`_.
 
 * The last argument to these intrinsics is a boolean flag
   indicating support for cache_hint. This flag argument must
@@ -1214,6 +1333,8 @@ Syntax:
   declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.tile.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
   declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.tile.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
 
+  declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.tile.gather4.2d(ptr %tensor_map, i32 %x0, i32 %y0, i32 %y1, i32 %y2, i32 %y3, i64 %ch, i1 %flag_ch)
+
 Overview:
 """""""""
 
@@ -1225,6 +1346,13 @@ multi-dimensional layout of the source tensor is preserved at the destination.
 The dimension of the tensor data ranges from 1d to 5d with the coordinates
 specified by the ``i32 %d0 ... i32 %d4`` arguments.
 
+In ``tile.gather4`` mode, four rows in the 2-dimnesional source tensor are
+fetched to the L2 cache. The first coordinate ``i32 %x0`` denotes the column index
+followed by four coordinates indicating the four row-indices. So, this mode takes
+a total of 5 coordinates as input arguments.
+For more information on ``gather4`` mode, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/#tensor-tiled-scatter4-gather4-modes>`_.
+
 * The last argument to these intrinsics is a boolean flag
   indicating support for cache_hint. This flag argument must
   be a compile-time constant. When set, it indicates a valid
@@ -1246,6 +1374,14 @@ Syntax:
   declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i16 %im2col0, i16 %im2col1, ...)
   declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, i16 %im2col0, i16 %im2col1, i16 %im2col2, ...)
 
+  declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.w.3d(ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %wHalo, i16 %wOffset, i64 %ch, i1 %flag_ch)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.w.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.w.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
+
+  declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.w.128.3d(ptr %tensor_map, i32 %d0, i32 %d1, i32 %d2, i16 %wHalo, i16 %wOffset, i64 %ch, i1 %flag_ch)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.w.128.4d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, ...)
+  declare void @llvm.nvvm.cp.async.bulk.tensor.prefetch.im2col.w.128.5d(..., i32 %d0, i32 %d1, i32 %d2, i32 %d3, i32 %d4, ...)
+
 Overview:
 """""""""
 
@@ -1256,9 +1392,16 @@ of tensor data from global memory to the L2 cache. In im2col mode, some
 dimensions of the source tensor are unrolled into a single dimensional
 column at the destination. In this mode, the tensor has to be at least
 three-dimensional. Along with the tensor coordinates, im2col offsets are
-also specified (denoted by ``i16 im2col0...i16 %im2col2``). The number
-of im2col offsets is two less than the number of dimensions of the tensor
-operation. The last argument to these intrinsics is a boolean flag, with
+also specified (denoted by ``i16 im2col0...i16 %im2col2``). For ``im2col``
+mode, the number of offsets is two less than the number of dimensions of
+the tensor operation. For the ``im2col.w`` and ``im2col.w.128`` modes,
+the number of offsets is always 2, denoted by ``i16 %wHalo`` and
+``i16 %wOffset`` arguments. For more information on ``im2col.w`` and
+``im2col.w.128`` modes, refer PTX ISA
+`<https://docs.nvidia.com/cuda/parallel-thread-execution/#tensor-im2col-w-w128-modes>`_.
+
+
+The last argument to these intrinsics is a boolean flag, with
 the same functionality as described in the ``tile`` mode intrinsics above.
 
 For more information, refer PTX ISA