chore: import upstream snapshot with attribution

2026-07-13 13:36:25 +08:00
commit 26446540fa
3151 changed files with 974126 additions and 0 deletions
@@ -0,0 +1,112 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=invalid-name,missing-function-docstring
+"""Intrinsics for x86 tensorization."""
+
+from tvm.script import tirx as T
+
+from .. import TensorIntrin
+
+# Tensorized intrinsic description and VNNI-specific implementation.
+# Equivalent to the ones in topi/x86/tensor_intrin.py
+
+
+@T.prim_func(s_tir=True)
+def dot_product_16x4_u8i8i32_desc(
+    A: T.Buffer((4,), "uint8", offset_factor=1),
+    B: T.Buffer((16, 4), "int8", offset_factor=1),
+    C: T.Buffer((16,), "int32", offset_factor=1),
+) -> None:
+    with T.sblock("root"):
+        T.reads(C[0:16], A[0:4], B[0:16, 0:4])
+        T.writes(C[0:16])
+        for i in T.serial(0, 16):
+            for k in T.serial(0, 4):
+                with T.sblock("update"):
+                    vi, vk = T.axis.remap("SR", [i, k])
+                    C[vi] = C[vi] + T.cast(A[vk], "int32") * T.cast(B[vi, vk], "int32")
+
+
+@T.prim_func(s_tir=True)
+def dot_product_16x4_u8i8i32_vnni(
+    A: T.Buffer((4,), "uint8", offset_factor=1),
+    B: T.Buffer((16, 4), "int8", offset_factor=1),
+    C: T.Buffer((16,), "int32", offset_factor=1),
+) -> None:
+    with T.sblock("root"):
+        T.reads(C[0:16], A[0:4], B[0:16, 0:4])
+        T.writes(C[0:16])
+
+        A_u8x4 = A.vload([0], "uint8x4")
+        A_i32 = T.reinterpret(A_u8x4, dtype="int32")
+
+        B_i8x64 = B.vload([0, 0], dtype="int8x64")
+        B_i32x16 = T.reinterpret(B_i8x64, dtype="int32x16")
+        C_i32x16 = C.vload([0], dtype="int32x16")
+
+        C[T.ramp(T.int32(0), 1, 16)] = T.call_llvm_pure_intrin(
+            T.llvm_lookup_intrinsic_id("llvm.x86.avx512.vpdpbusd.512"),
+            C_i32x16,
+            T.broadcast(A_i32, 16),
+            B_i32x16,
+            dtype="int32x16",
+        )
+
+
+@T.prim_func(s_tir=True)
+def dot_product_16x4_u8i8i32_avx512(
+    A: T.Buffer((4,), "uint8", offset_factor=1),
+    B: T.Buffer((16, 4), "int8", offset_factor=1),
+    C: T.Buffer((16,), "int32", offset_factor=1),
+) -> None:
+    with T.sblock("root"):
+        T.reads(C[0:16], A[0:4], B[0:16, 0:4])
+        T.writes(C[0:16])
+
+        A_u8x4 = A.vload([0], "uint8x4")
+        A_i32 = T.reinterpret(A_u8x4, dtype="int32")
+        A_brdcst = T.broadcast(A_i32, 16)
+        A_u8x64 = T.reinterpret(A_brdcst, dtype="uint8x64")
+
+        B_i8x64 = B.vload([0, 0], dtype="int8x64")
+
+        Red = T.call_llvm_pure_intrin(
+            T.llvm_lookup_intrinsic_id("llvm.x86.avx512.pmaddubs.w.512"),
+            A_u8x64,
+            B_i8x64,
+            dtype="int16x32",
+        )
+
+        C[T.ramp(T.int32(0), 1, 16)] += T.call_llvm_pure_intrin(
+            T.llvm_lookup_intrinsic_id("llvm.x86.avx512.pmaddw.d.512"),
+            Red,
+            T.int16x32(1),
+            dtype="int32x16",
+        )
+
+
+VNNI_DOT_16x4_INTRIN = "dot_16x4_vnni"
+
+TensorIntrin.register(
+    VNNI_DOT_16x4_INTRIN, dot_product_16x4_u8i8i32_desc, dot_product_16x4_u8i8i32_vnni
+)
+
+AVX512_DOT_16x4_INTRIN = "dot_16x4_avx512"
+
+TensorIntrin.register(
+    AVX512_DOT_16x4_INTRIN, dot_product_16x4_u8i8i32_desc, dot_product_16x4_u8i8i32_avx512
+)