)]}' { "commit": "09685ee644d2d5676f9566e3275bca566efe547d", "tree": "33c3357a2b24a6c9fb1ab8c7aa4466fe28de8fee", "parents": [ "49335b7ee56d3d3b58b0850a3dbba3e179524739" ], "author": { "name": "bjacob", "email": "benoitjacob@google.com", "time": "Sun Jul 16 23:50:11 2023 -0400" }, "committer": { "name": "GitHub", "email": "noreply@github.com", "time": "Sun Jul 16 23:50:11 2023 -0400" }, "message": "data-tiling: introduce `upper_bound_tile_size` op to defer padding-size choice to MaterializeEncoding. (#14349)\n\nThis fixes #11632, by introducing a materializable\r\n`upper_bound_tile_size ` instead of hardcoding a fixed padding amount at\r\nFlow, and fixes it in sufficient generality to also solve the problem\r\nfor narrow matmuls - let\u0027s explain that in more detail as this is an\r\nimportant part of what this PR is doing.\r\n\r\nFor each combination of element types and each target, the\r\nMaterializeEncoding pass selects appropriate matmul tile shapes. Input\r\ntensors get padded to the next multiple of the next tile size. The\r\npadding increases the inherent arithmetic cost of the problem at hand.\r\nWhen, along some dimension, the original tensor size is smaller than the\r\ntile size, that can result in particulary large overhead. The extreme\r\ncase, which is also a very common case, is matrix-times-vector\r\nmultiplication. The \"vector\" right-hand side is really a matrix with one\r\ndimension size equal to 1, so if the general matmul tile shape along\r\nthat dimension is 8 or 16, as is usually the case, that can be a 8x or\r\n16x increase in the inherent arithmetic cost of the matmul op.\r\n\r\nThe solution to that is to adjust MaterializeEncoding tile shapes to\r\nnarrow dimensions. We had some logic in place to deal with that, but\r\n#11632 was leaving it moot: the flow-level padding of everything to the\r\nnext multiple of 16 meant that our logic there never really had a chance\r\nof kicking in. With #11632 being fixed, this PR was the opportunity to\r\nalso fix that along the way, and to ensure that the solution to #11632\r\nworked also in that respect. As matrix-times-vector products were the\r\ncommon case that suffered the most from #11632, it would have been too\r\nbad to \"solve\" #11632 without addressing that. By the way,\r\nmatrix-times-vector is only the extreme case, but other narrow cases\r\nmatter too. When, e.g. on AVX-512, the general matmul tile size is 16,\r\neven width-8 matmuls (MxKx8) were suffering from 2x-widening. So the\r\nsolution in this PR is making sure to address all narrow cases, defined\r\nas whenever a tensor dimension size is less than the general tile size.\r\n\r\nThe difficulty was that when MaterializeEncoding runs on a dispatch\r\nfunction, it runs on an already-padded tensor; even as this PR\r\nintroduces `upper_bound_tile_size`, that only makes it possible to\r\nselect the right padding amount, but there\u0027s still a `tensor.pad` op and\r\nit\u0027s still getting in the way of knowing the actual, original tensor\r\nshape for the purpose of adjusting tile shapes for narrow cases.\r\nMoreover, as `MaterializeEncoding` is a type-converter pass, it can\u0027t\r\njust walk from a Value up to its defining-op to find the pre-padding\r\ntensor. There are no values there, only types. So the information about\r\nthe pre-padding tensor shape has to be part of the tensor type that\r\n`MaterializeEncoding` sees, that its, the padded tensor type.\r\n\r\nThe solution to that problem in this PR is to add a `original_type`\r\nfield to `EncodingAttr`.\r\n\r\nFixes #11632.\r\n\r\nFixes a compiler issue encountered in #14398 but not the originally\r\nreported runtime crash by itself.\r\n\r\nThis now also includes the removal of a now-useless VMVX pass, which was\r\noriginally split into https://github.com/openxla/iree/pull/14383 .", "tree_diff": [ { "type": "modify", "old_id": "5d6a3fcdc91f5e8bdcc0fbda63a41eb8bd525f2c", "old_mode": 33188, "old_path": "compiler/src/iree/compiler/Codegen/BUILD.bazel", "new_id": "a2c7bdcf456e48f4c222e3378660500751449f29", "new_mode": 33188, "new_path": "compiler/src/iree/compiler/Codegen/BUILD.bazel" }, { "type": "modify", "old_id": "40dc1734eb788e54f8e684d254ff92884c793c86", "old_mode": 33188, "old_path": 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