[SME] Add scalable fp16->fp32 dense schedule #16981
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This commit extends the functionality of the SME dense and matmul schedules to support operations with fp16 inputs and an fp32 output, where `transpose_a=False` and `transpose_b=True`. For convenience, it also adds a utility called `get_vscale_factor` which created the correct multiplier for `vscale` given a data type, reflecting ideas from an early design of the [SVE](apache/tvm-rfcs#104) RFC. Change-Id: I8c00bc6baf2df6015fa41200a238781126c73589
Change-Id: Ie7fb7a0a76119aa5c82e03ea0b2cc10de9f15f5e
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Change-Id: I0e9e45b285082b42676e53e74158e11d7e08608b
Change-Id: I32273241ae7569b65e082759e4f2ca4355ac6933
Change-Id: I237b4c5cb5ca22e33529d98cbd75177b94904857
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@tvm-bot rerun |
ekalda
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May 28, 2024
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Thanks @lhutton1 this is merged now! |
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Fixes a merge conflict between apache#16981 and apache#17003. Change-Id: Ifcc983ef0b8c00250568a048fd682933adfdcde4
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This commit extends the SME conv2d NHWC schedule to support convolutions with float16 inputs (data and kernel) and a float32 output using the tensor intrinsics added in apache#16981.
ekalda
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This commit extends the SME conv2d NHWC schedule to support convolutions with float16 inputs (data and kernel) and a float32 output using the tensor intrinsics added in #16981.
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This commit extends the functionality of the SME dense and matmul schedules to support operations with fp16 inputs and an fp32 output, where
transpose_a=Falseandtranspose_b=True.For convenience, it also adds a utility called
get_vscale_factorwhich creates the correct multiplier forvscalegiven a data type, reflecting ideas from an early design of the SVE RFC.Note: this commit depends on #16921 so also contains the contents of #16921.