def generate_emulate(self, result, mpfr_x, mpfr_rnd):
""" generate the emulation code for ML_Log2 functions
mpfr_x is a mpfr_t variable which should have the right precision
mpfr_rnd is the rounding mode
"""
emulate_func_name = "mpfr_acos"
emulate_func_op = FunctionOperator(emulate_func_name, arg_map = {0: FO_Result(0), 1: FO_Arg(0), 2: FO_Arg(1)}, require_header = ["mpfr.h"])
emulate_func = FunctionObject(emulate_func_name, [ML_Mpfr_t, ML_Int32], ML_Mpfr_t, emulate_func_op)
mpfr_call = Statement(ReferenceAssign(result, emulate_func(mpfr_x, mpfr_rnd)))
return mpfr_call
def __init__(self, pattern, arity=1, exu=None, **kw):
TemplateOperatorFormat.__init__(
self,
pattern,
arg_map=({
index: arg_obj
for (index,
arg_obj) in [(0, FO_Result())] + [(i + 1, FO_Arg(i))
for i in range(arity)]
}),
*kw)
MachineInstruction.__init__(self, exu)
def generate_scheme(self):
#func_implementation = CodeFunction(self.function_name, output_format = self.precision)
vx = self.implementation.add_input_variable("x", self.get_input_precision())
mpfr_x = Conversion(vx, precision = ML_Mpfr_t)
emulate_func_name = "mpfr_exp"
emulate_func_op = FunctionOperator(emulate_func_name, arg_map = {0: FO_Result(0), 1: FO_Arg(0)}, require_header = ["mpfr.h"])
emulate_func = FunctionObject(emulate_func_name, [ML_Mpfr_t], ML_Mpfr_t, emulate_func_op)
emulate_func_op.declare_prototype = emulate_func
mpfr_call = Conversion(emulate_func(mpfr_x), precision = self.precision)
scheme = Statement(Return(mpfr_call))
return scheme
def generate_emulate(self, result, mpfr_x, mpfr_rnd):
""" generate the emulation code for ML_Log2 functions
mpfr_x is a mpfr_t variable which should have the right precision
mpfr_rnd is the rounding mode
"""
#mpfr_x = emulate_implementation.add_input_variable("x", ML_Mpfr_t)
#mpfr_rnd = emulate_implementation.add_input_variable("rnd", ML_Int32)
emulate_func_name = "mpfr_log10"
emulate_func_op = FunctionOperator(emulate_func_name,
arg_map={
0: FO_Result(0),
1: FO_Arg(0),
2: FO_Arg(1)
},
require_header=["mpfr.h"])
emulate_func = FunctionObject(emulate_func_name, [ML_Mpfr_t, ML_Int32],
ML_Mpfr_t, emulate_func_op)
#emulate_func_op.declare_prototype = emulate_func
mpfr_call = Statement(
ReferenceAssign(result, emulate_func(mpfr_x, mpfr_rnd)))
return mpfr_call
StandardAsmOperator("faddd {} = {}, {}", arity=2, exu=DA_FPU),
type_strict_match(v4float32, v4float32, v4float32):
StandardAsmOperator("faddwq {} = {}, {}", arity=2, exu=DA_FPU),
},
},
},
Subtraction: {
None: {
lambda _: True: {
type_strict_match_list([ML_Int32, ML_UInt32], [
ML_UInt32, ML_Int32
], [ML_Int32, ML_UInt32]):
# subtract from: op1 - op0 (reverse)
AdvancedAsmOperator("sbfw {} = {}, {}",
arg_map={
0: FO_Result(),
1: FO_Arg(1),
2: FO_Arg(0)
},
arity=2,
exu=DA_ALU),
type_strict_match(ML_Binary32, ML_Binary32, ML_Binary32):
# subtract from: op1 - op0 (reverse)
AdvancedAsmOperator("fsbfw {} = {}, {}",
arg_map={
0: FO_Result(),
1: FO_Arg(1),
2: FO_Arg(0)
},
arity=2,
exu=DA_FPU),