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from typing import Tuple |
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import cutlass |
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import cutlass.cute as cute |
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from cutlass import Int32, Uint32 |
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from cutlass.cutlass_dsl import T, dsl_user_op |
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from cutlass._mlir.dialects import llvm |
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@cute.jit |
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def clz(x: Int32) -> Int32: |
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res = Int32(32) |
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done = False |
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for i in cutlass.range(32): |
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if ((1 << (31 - i)) & x) and not done: |
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res = Int32(i) |
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done = True |
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return res |
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def find_log2(x: Int32) -> Int32: |
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a: Int32 = Int32(31 - clz(x)) |
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return a + ((x & (x - 1)) != 0) |
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@dsl_user_op |
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def umulhi(a: Int32, b: Int32, *, loc=None, ip=None) -> Uint32: |
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return Uint32( |
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llvm.inline_asm( |
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T.i32(), |
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[Int32(a).ir_value(loc=loc, ip=ip), Int32(b).ir_value(loc=loc, ip=ip)], |
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"mul.hi.u32 $0, $1, $2;", |
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"=r,r,r", |
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has_side_effects=False, |
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is_align_stack=False, |
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asm_dialect=llvm.AsmDialect.AD_ATT, |
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) |
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) |
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class FastDivmod: |
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def __init__( |
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self, divisor: Int32, multipler: Uint32, shift_right: Uint32, *, loc=None, ip=None |
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): |
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self.divisor = divisor |
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self.multiplier = multipler |
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self.shift_right = shift_right |
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self._loc = loc |
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@staticmethod |
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def create(divisor: Int32, *, loc=None, ip=None) -> "FastDivmod": |
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"""Construct the FastDivmod object, in host code. |
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This precomputes some values based on the divisor and is computationally expensive. |
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""" |
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p = Uint32(31 + find_log2(divisor)) |
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divisor_u32 = Uint32(divisor) |
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multiplier = Uint32(((cutlass.Uint64(1) << p) + divisor_u32 - 1) // divisor_u32) |
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shift_right = Uint32(p - 32) |
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return FastDivmod(divisor, multiplier, shift_right, loc=loc, ip=ip) |
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@cute.jit |
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def div(self, dividend: Int32) -> Int32: |
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return ( |
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Int32(umulhi(dividend, self.multiplier) >> self.shift_right) |
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if self.divisor != 1 |
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else dividend |
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) |
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def divmod(self, dividend: Int32) -> Tuple[Int32, Int32]: |
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quotient = self.div(dividend) |
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remainder = dividend - quotient * self.divisor |
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return quotient, remainder |
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def __extract_mlir_values__(self): |
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values, self._values_pos = [], [] |
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for obj in [self.divisor, self.multiplier, self.shift_right]: |
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obj_values = cutlass.extract_mlir_values(obj) |
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values += obj_values |
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self._values_pos.append(len(obj_values)) |
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return values |
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def __new_from_mlir_values__(self, values): |
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obj_list = [] |
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for obj, n_items in zip( |
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[self.divisor, self.multiplier, self.shift_right], self._values_pos |
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): |
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obj_list.append(cutlass.new_from_mlir_values(obj, values[:n_items])) |
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values = values[n_items:] |
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return FastDivmod(*(tuple(obj_list)), loc=self._loc) |
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