IntrinsicFunction¶
An intrinsic function. An expr node.
Declaration¶
Sintaxe¶
IntrinsicFunction(expr* args, int intrinsic_id, int overload_id,
ttype type, expr? value)
Argumentos¶
args
represents all arguments passed to the functionintrinsic_id
is the unique ID of the generic intrinsic functionoverload_id
is the ID of the signature within the given generic functiontype
represents the type of the outputvalue
is an optional compile time value
Valores de retorno¶
The return value is the expression that the IntrinsicFunction
represents.
Descrição¶
IntrinsicFunction represents an intrinsic function (such as Abs
,
Modulo
, Sin
, Cos
, LegendreP
, FlipSign
, …) that either the backend
or the middle-end (optimizer) needs to have some special logic for. Typically a
math function, but does not have to be.
IntrinsicFunction is both side-effect-free (no writes to global variables) and deterministic (no reads from global variables). They can be used inside parallel code and cached. There are two kinds:
elemental
: the function is defined as a scalar function and it can be vectorized over any argument(s). Examples:Sin
,Cos
,LegendreP
,Abs
non-elemental
: it accepts arrays as arguments and the function cannot be defined as a scalar function. Examples:Sum
,Any
,MinLoc
The intrinsic_id
determines the generic function uniquely (Sin
and Abs
have different number, but IntegerAbs
and RealAbs
share the number) and
overload_id
uniquely determines the signature starting from 0 for each
generic function (e.g., IntegerAbs
, RealAbs
and ComplexAbs
can have
overload_id
equal to 0, 1 and 2, and RealSin
, ComplexSin
can be 0, 1).
Backend use cases: Some architectures have special hardware instructions for
operations like Sqrt or Sin and if they are faster than a software
implementation, the backend will use it. This includes the FlipSign
function
which is our own «special function» that the optimizer emits for certain
conditional floating point operations, and the backend emits an efficient bit
manipulation implementation for architectures that support it.
Middle-end use cases: the middle-end can use the high level semantics to
simplify, such as sin(e)**2 + cos(e)**2 -> 1
, or it could approximate
expressions like if (abs(sin(x) - 0.5) < 0.3)
with a lower accuracy version
of sin
.
We provide ASR -> ASR lowering transformations that substitute the given
intrinsic function with an ASR implementation using more primitive ASR nodes,
typically implemented in the surface language (say a sin
implementation using
argument reduction and a polynomial fit, or a sqrt
implementation using a
general power formula x**(0.5)
, or LegendreP(2,x)
implementation using a
formula (3*x**2-1)/2
).
This design also makes it possible to allow selecting using command line
options how certain intrinsic functions should be implemented, for example if
trigonometric functions should be implemented using our own fast
implementation, libm
accurate implementation, we could also call into other
libraries. These choices should happen at the ASR level, and then the result
further optimized (such as inlined) as needed.
Tipos¶
The argument types in args
have the types of the corresponding signature as
determined by intrinsic_id
. For example IntegerAbs
accepts an integer, but
RealAbs
accepts a real.
Exemplos¶
The following example code creates IntrinsicFunction
ASR node:
sin(0.5)
ASR:
(TranslationUnit
(SymbolTable
1
{
})
[(IntrinsicFunction
[(RealConstant
0.500000
(Real 4 [])
)]
0
0
(Real 4 [])
(RealConstant 0.479426 (Real 4 []))
)]
)