In an effort to get this thread back on track, I tried implementing cos(_:)
in pure generic Swift code, with the BinaryFloatingPoint protocol. It
deviates from the _cos(_:) intrinsic by no more than 5.26362703423544e-11.
Adding more terms to the approximation only has a small penalty to the
performance for some reason.
To make the benchmarks fair, and explore the idea of distributing a Math
module without killing people on the cross-module optimization boundary, I
enabled some of the unsafe compiler attributes. All of these benchmarks are
cross-module calls, as if the math module were downloaded as a dependency
in the SPM.
== Relative execution time (lower is better) ==
llvm intrinsic : 3.133
glibc cos() : 3.124
no attributes : 43.675
with specialization : 4.162
with inlining : 3.108
with inlining and specialization : 3.264
As you can see, the pure Swift generic implementation actually beats the
compiler intrinsic (and the glibc cos() but I guess they’re the same thing)
when inlining is used, but for some reason generic specialization and
inlining don’t get along very well.
Here’s the source implementation. It uses a taylor series (!) which
probably isn’t optimal but it does prove that cos() and sin() can be
implemented as generics in pure Swift, be distributed as a module outside
the stdlib, and still achieve competitive performance with the llvm
intrinsics.
@_inlineable
//@_specialize(where F == Float)
//@_specialize(where F == Double)
public
func cos<F>(_ x:F) -> F where F:BinaryFloatingPoint
{
let x:F = abs(x.remainder(dividingBy: 2 * F.pi)),
quadrant:Int = Int(x * (2 / F.pi))
switch quadrant
{
case 0:
return cos(on_first_quadrant: x)
case 1:
return -cos(on_first_quadrant: F.pi - x)
case 2:
return -cos(on_first_quadrant: x - F.pi)
case 3:
return -cos(on_first_quadrant: 2 * F.pi - x)
default:
fatalError("unreachable")
}
}
@_versioned
@_inlineable
//@_specialize(where F == Float)
//@_specialize(where F == Double)
func cos<F>(on_first_quadrant x:F) -> F where F:BinaryFloatingPoint
{
let x2:F = x * x
var y:F = -0.0000000000114707451267755432394
for c:F in [0.000000002087675698165412591559,
-0.000000275573192239332256421489,
0.00002480158730158702330045157,
-0.00138888888888888880310186415,
0.04166666666666666665319411988,
-0.4999999999999999999991637437,
0.9999999999999999999999914771
]
{
y = x2 * y + c
}
return y
}
On Thu, Aug 3, 2017 at 7:04 AM, Stephen Canon via swift-evolution <
swift-evolution@swift.org> wrote:
> On Aug 2, 2017, at 7:03 PM, Karl Wagner via swift-evolution <
> swift-evolution@swift.org> wrote:
>
>
> It’s important to remember that computers are mathematical machines, and
> some functions which are implemented in hardware on essentially every
> platform (like sin/cos/etc) are definitely best implemented as compiler
> intrinsics.
>
>
> sin/cos/etc are implemented in software, not hardware. x86 does have the
> FSIN/FCOS instructions, but (almost) no one actually uses them to implement
> the sin( ) and cos( ) functions; they are a legacy curiosity, both too slow
> and too inaccurate for serious use today. There are no analogous
> instructions on ARM or PPC.
>
> – Steve
>
> _______________________________________________
> swift-evolution mailing list
> swift-evolution@swift.org
> https://lists.swift.org/mailman/listinfo/swift-evolution
>
>
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