Yet more definitions moved into the stdlib (#1263)

The only big catch that I ran into with this batch was that I found the `float.getPi()` function was being emitted to the output GLSL even when that function wasn't being used. This seems to have been a latent problem in the earlier PR, but was only surfaced in the tests once a Slang->GLSL test started using another intrinsic that led to the `float : __BuiltinFloatingPointType` witness table being live in the IR.

The fix for the gotcha here was to add a late IR pass that basically empties out all witness tables in the IR, so that functions that are only referenced by witness tables can then be removed as dead code. This pass is something we should *not* apply if/when we start supporting real dynamic dispatch through witness tables, but that is a problem to be solved on another day.

The remaining tricky pieces of this change were:

* Needed to remember to mark functions as target intrinsics on HLSL and/or GLSL as appropriate (hopefully I caught all the cases) so they don't get emitted as source there.

* The `msad4` function in HLSL is very poorly documented, so filling in its definition was tricky. I made my best effort based on how it is described on MSDN, but it is likely that if anybody wants to rely on this function they will need us to vet our results with some tests.

1 files changed, 148 insertions, 54 deletions

diff --git a/source/slang/hlsl.meta.slang b/source/slang/hlsl.meta.slang
index 572b64b21..d9e40dd4f 100644
--- a/source/slang/hlsl.meta.slang
+++ b/source/slang/hlsl.meta.slang
@@ -1199,9 +1199,24 @@ matrix<T, N, M> floor(matrix<T, N, M> x)
 }
 
 // Fused multiply-add for doubles
+__target_intrinsic(hlsl)
+__target_intrinsic(glsl)
 double fma(double a, double b, double c);
-__generic<let N : int> vector<double, N> fma(vector<double, N> a, vector<double, N> b, vector<double, N> c);
-__generic<let N : int, let M : int> matrix<double,N,M> fma(matrix<double,N,M> a, matrix<double,N,M> b, matrix<double,N,M> c);
+
+__generic<let N : int>
+__target_intrinsic(hlsl)
+__target_intrinsic(glsl)
+vector<double, N> fma(vector<double, N> a, vector<double, N> b, vector<double, N> c)
+{
+    VECTOR_MAP_TRINARY(double, N, fma, a, b, c);
+}
+
+__generic<let N : int, let M : int>
+__target_intrinsic(hlsl)
+matrix<double, N, M> fma(matrix<double, N, M> a, matrix<double, N, M> b, matrix<double, N, M> c)
+{
+    MATRIX_MAP_TRINARY(double, N, M, fma, a, b, c);
+}
 
 // Floating point remainder of x/y
 __generic<T : __BuiltinFloatingPointType>
@@ -1425,7 +1440,6 @@ __generic<T : __BuiltinFloatingPointType>
 __target_intrinsic(hlsl)
 __target_intrinsic(cpu)
 __target_intrinsic(cuda)
-//__target_intrinsic(glsl, "(!(isinf($0) || isnan($0)))")
 bool isfinite(T x)
 {
     return !(isinf(x) || isnan(x));
@@ -1433,7 +1447,6 @@ bool isfinite(T x)
 
 __generic<T : __BuiltinFloatingPointType, let N : int>
 __target_intrinsic(hlsl)
-//__target_intrinsic(glsl, "(!(isinf($0) || isnan($0)))")
 vector<bool, N> isfinite(vector<T, N> x)
 {
     VECTOR_MAP_UNARY(bool, N, isfinite, x);
@@ -1488,18 +1501,16 @@ matrix<bool, N, M> isnan(matrix<T, N, M> x)
 
 __generic<T : __BuiltinFloatingPointType>
 __target_intrinsic(hlsl)
-__target_intrinsic(glsl, "($0 * pow(2.0f, $1))")
-T ldexp(T x, T exp);
-/*{
+T ldexp(T x, T exp)
+{
     return x * exp2(exp);
-}*/
+}
 
 __generic<T : __BuiltinFloatingPointType, let N : int>
 __target_intrinsic(hlsl)
-__target_intrinsic(glsl, "($0 * pow(2.0f, $1))")
 vector<T, N> ldexp(vector<T, N> x, vector<T, N> exp)
 {
-    VECTOR_MAP_BINARY(T, N, ldexp, x, exp);
+    return x * exp2(exp);
 }
 
 __generic<T : __BuiltinFloatingPointType, let N : int, let M : int>
@@ -1522,17 +1533,17 @@ T length(vector<T, N> x)
 __generic<T : __BuiltinFloatingPointType>
 __target_intrinsic(hlsl)
 __target_intrinsic(glsl, mix)
-T lerp(T x, T y, T s);
-/*{
-    return x * (1 - s) + y * s;
-}*/
+T lerp(T x, T y, T s)
+{
+    return x * (T(1.0f) - s) + y * s;
+}
 
 __generic<T : __BuiltinFloatingPointType, let N : int>
 __target_intrinsic(hlsl)
 __target_intrinsic(glsl, mix)
 vector<T, N> lerp(vector<T, N> x, vector<T, N> y, vector<T, N> s)
 {
-    VECTOR_MAP_TRINARY(T, N, lerp, x, y, s);
+    return x * (T(1.0f) - s) + y * s;
 }
 
 __generic<T : __BuiltinFloatingPointType, let N : int, let M : int>
@@ -1543,7 +1554,14 @@ matrix<T,N,M> lerp(matrix<T,N,M> x, matrix<T,N,M> y, matrix<T,N,M> s)
 }
 
 // Legacy lighting function (obsolete)
-float4 lit(float n_dot_l, float n_dot_h, float m);
+__target_intrinsic(hlsl)
+float4 lit(float n_dot_l, float n_dot_h, float m)
+{
+    let ambient = 1.0f;
+    let diffuse = max(n_dot_l, 0.0f);
+    let specular = step(0.0f, n_dot_l) * max(n_dot_h * m, 0.0f);
+    return float4(ambient, diffuse, specular, 1.0f);
+}
 
 // Base-e logarithm
 __generic<T : __BuiltinFloatingPointType>
@@ -1606,14 +1624,25 @@ matrix<T,N,M> log2(matrix<T,N,M> x)
 
 // multiply-add
 
+__generic<T : __BuiltinArithmeticType>
+__target_intrinsic(hlsl)
 __target_intrinsic(glsl, fma)
-__generic<T : __BuiltinArithmeticType> T mad(T mvalue, T avalue, T bvalue);
+T mad(T mvalue, T avalue, T bvalue);
 
+__generic<T : __BuiltinArithmeticType, let N : int>
+__target_intrinsic(hlsl)
 __target_intrinsic(glsl, fma)
-__generic<T : __BuiltinArithmeticType, let N : int> vector<T,N> mad(vector<T,N> mvalue, vector<T,N> avalue, vector<T,N> bvalue);
+vector<T, N> mad(vector<T, N> mvalue, vector<T, N> avalue, vector<T, N> bvalue)
+{
+    VECTOR_MAP_TRINARY(T, N, mad, mvalue, avalue, bvalue);
+}
 
-__target_intrinsic(glsl, fma)
-__generic<T : __BuiltinArithmeticType, let N : int, let M : int> matrix<T,N,M> mad(matrix<T,N,M> mvalue, matrix<T,N,M> avalue, matrix<T,N,M> bvalue);
+__generic<T : __BuiltinArithmeticType, let N : int, let M : int>
+__target_intrinsic(hlsl)
+matrix<T, N, M> mad(matrix<T, N, M> mvalue, matrix<T, N, M> avalue, matrix<T, N, M> bvalue)
+{
+    MATRIX_MAP_TRINARY(T, N, M, mad, mvalue, avalue, bvalue);
+}
 
 // maximum
 __generic<T : __BuiltinArithmeticType>
@@ -1677,32 +1706,79 @@ matrix<T,N,M> modf(matrix<T,N,M> x, out matrix<T,N,M> ip)
 }
 
 // msad4 (whatever that is)
-uint4 msad4(uint reference, uint2 source, uint4 accum);
+__target_intrinsic(hlsl)
+uint4 msad4(uint reference, uint2 source, uint4 accum)
+{
+    int4 bytesRef = (reference >> uint4(24, 16, 8, 0)) & 0xFF;
+    int4 bytesX   = (source.x  >> uint4(24, 16, 8, 0)) & 0xFF;
+    int4 bytesY   = (source.y  >> uint4(24, 16, 8, 0)) & 0xFF;
+
+    uint4 mask = bytesRef == 0 ? 0 : 0xFFFFFFFFu;
+
+    uint4 result = accum;
+    result += mask.x & abs(bytesRef - int4(bytesX.x,           bytesY.y, bytesY.z, bytesY.w));
+    result += mask.y & abs(bytesRef - int4(bytesX.x, bytesX.y,           bytesY.z, bytesY.w));
+    result += mask.z & abs(bytesRef - int4(bytesX.x, bytesX.y, bytesX.z,           bytesY.w));
+    result += mask.w & abs(bytesRef - int4(bytesX.x, bytesX.y, bytesX.z, bytesX.w));
+    return result;
+}
 
 // General inner products
 
 // scalar-scalar
-__generic<T : __BuiltinArithmeticType> T mul(T x, T y);
+__generic<T : __BuiltinArithmeticType>
+__intrinsic_op($(kIROp_Mul))
+T mul(T x, T y);
 
 // scalar-vector and vector-scalar
-__generic<T : __BuiltinArithmeticType, let N : int> vector<T,N> mul(vector<T,N> x, T y);
-__generic<T : __BuiltinArithmeticType, let N : int> vector<T,N> mul(T x, vector<T,N> y);
+__generic<T : __BuiltinArithmeticType, let N : int>
+__intrinsic_op($(kIROp_Mul))
+vector<T, N> mul(vector<T, N> x, T y);
+
+__generic<T : __BuiltinArithmeticType, let N : int>
+__intrinsic_op($(kIROp_Mul))
+vector<T, N> mul(T x, vector<T, N> y);
 
 // scalar-matrix and matrix-scalar
-__generic<T : __BuiltinArithmeticType, let N : int, let M :int> matrix<T,N,M> mul(matrix<T,N,M> x, T y);
-__generic<T : __BuiltinArithmeticType, let N : int, let M :int> matrix<T,N,M> mul(T x, matrix<T,N,M> y);
+__generic<T : __BuiltinArithmeticType, let N : int, let M :int>
+__intrinsic_op($(kIROp_Mul))
+matrix<T, N, M> mul(matrix<T, N, M> x, T y);
+
+__generic<T : __BuiltinArithmeticType, let N : int, let M :int>
+__intrinsic_op($(kIROp_Mul))
+matrix<T, N, M> mul(T x, matrix<T, N, M> y);
 
 // vector-vector (dot product)
-__generic<T : __BuiltinArithmeticType, let N : int> __intrinsic_op(dot) T mul(vector<T,N> x, vector<T,N> y);
+__generic<T : __BuiltinArithmeticType, let N : int>
+__target_intrinsic(hlsl)
+__target_intrinsic(glsl, "dot")
+T mul(vector<T, N> x, vector<T, N> y)
+{
+    return dot(x, y);
+}
+
+${{{{
+// TODO: The following functions could conceivably be defined
+// in the stdlib for the benefit of targets without direct
+// support for matrices, but the use of `__intrinsic_op` to
+// map them to a dedicated IR instruction interferes with
+// that choice.
+}}}}
 
 // vector-matrix
-__generic<T : __BuiltinArithmeticType, let N : int, let M : int> __intrinsic_op(mulVectorMatrix) vector<T,M> mul(vector<T,N> x, matrix<T,N,M> y);
+__generic<T : __BuiltinArithmeticType, let N : int, let M : int>
+__intrinsic_op(mulVectorMatrix)
+vector<T,M> mul(vector<T,N> x, matrix<T,N,M> y);
 
 // matrix-vector
-__generic<T : __BuiltinArithmeticType, let N : int, let M : int> __intrinsic_op(mulMatrixVector) vector<T,N> mul(matrix<T,N,M> x, vector<T,M> y);
+__generic<T : __BuiltinArithmeticType, let N : int, let M : int>
+__intrinsic_op(mulMatrixVector)
+vector<T,N> mul(matrix<T,N,M> x, vector<T,M> y);
 
 // matrix-matrix
-__generic<T : __BuiltinArithmeticType, let R : int, let N : int, let C : int> __intrinsic_op(mulMatrixMatrix) matrix<T,R,C> mul(matrix<T,R,N> x, matrix<T,N,C> y);
+__generic<T : __BuiltinArithmeticType, let R : int, let N : int, let C : int>
+__intrinsic_op(mulMatrixMatrix)
+matrix<T,R,C> mul(matrix<T,R,N> x, matrix<T,N,C> y);
 
 // noise (deprecated)
 
@@ -1753,10 +1829,13 @@ int NonUniformResourceIndex(int index)
 }
 
 // Normalize a vector
-__generic<T : __BuiltinFloatingPointType, let N : int> vector<T,N> normalize(vector<T,N> x);
-/*{
+__generic<T : __BuiltinFloatingPointType, let N : int>
+__target_intrinsic(hlsl)
+__target_intrinsic(glsl)
+vector<T,N> normalize(vector<T,N> x)
+{
     return x / length(x);
-}*/
+}
 
 // Raise to a power
 __generic<T : __BuiltinFloatingPointType>
@@ -1856,31 +1935,33 @@ void ProcessTriTessFactorsMin(
 __generic<T : __BuiltinFloatingPointType>
 __target_intrinsic(hlsl)
 __target_intrinsic(glsl)
-T radians(T x);
+T radians(T x)
+{
+    return x * (T.getPi() / T(180.0f));
+}
 
 __generic<T : __BuiltinFloatingPointType, let N : int>
 __target_intrinsic(hlsl)
 __target_intrinsic(glsl)
 vector<T, N> radians(vector<T, N> x)
 {
-    VECTOR_MAP_UNARY(T, N, radians, x);
+    return x * (T.getPi() / T(180.0f));
 }
 
 __generic<T : __BuiltinFloatingPointType, let N : int, let M : int>
 __target_intrinsic(hlsl)
 matrix<T, N, M> radians(matrix<T, N, M> x)
 {
-    MATRIX_MAP_UNARY(T, N, M, radians, x);
+    return x * (T.getPi() / T(180.0f));
 }
 
 // Approximate reciprocal
 __generic<T : __BuiltinFloatingPointType>
 __target_intrinsic(hlsl)
-__target_intrinsic(glsl, "1.0/($0)")
-T rcp(T x);
-/*{
-    return T(1) / x;
-}*/
+T rcp(T x)
+{
+    return T(1.0) / x;
+}
 
 __generic<T : __BuiltinFloatingPointType, let N : int>
 __target_intrinsic(hlsl)
@@ -1891,7 +1972,6 @@ vector<T, N> rcp(vector<T, N> x)
 
 __generic<T : __BuiltinFloatingPointType, let N : int, let M : int>
 __target_intrinsic(hlsl)
-// Note: GLSL doesn't define a vector `rcp`, so not intrinsic there
 matrix<T, N, M> rcp(matrix<T, N, M> x)
 {
     MATRIX_MAP_UNARY(T, N, M, rcp, x);
@@ -1899,27 +1979,35 @@ matrix<T, N, M> rcp(matrix<T, N, M> x)
 
 // Reflect incident vector across plane with given normal
 __generic<T : __BuiltinFloatingPointType, let N : int>
-vector<T,N> reflect(vector<T,N> i, vector<T,N> n);
-/*{
+__target_intrinsic(hlsl)
+__target_intrinsic(glsl)
+vector<T,N> reflect(vector<T,N> i, vector<T,N> n)
+{
     return i - T(2) * dot(n,i) * n;
-}*/
+}
 
 // Refract incident vector given surface normal and index of refraction
 __generic<T : __BuiltinFloatingPointType, let N : int>
-vector<T,N> refract(vector<T,N> i, vector<T,N> n, float eta);
-/*{
+__target_intrinsic(hlsl)
+__target_intrinsic(glsl)
+vector<T,N> refract(vector<T,N> i, vector<T,N> n, T eta)
+{
     let dotNI = dot(n,i);
     let k = T(1) - eta*eta*(T(1) - dotNI * dotNI);
-    if(k < 0) return vector<T,N>(T(0));
+    if(k < T(0)) return vector<T,N>(T(0));
     return eta * i - (eta * dotNI + sqrt(k)) * n;
-}*/
+}
 
 // Reverse order of bits
 __target_intrinsic(glsl, "bitfieldReverse")
 uint reversebits(uint value);
 
 __target_intrinsic(glsl, "bitfieldReverse")
-__generic<let N : int> vector<uint,N> reversebits(vector<uint,N> value);
+__generic<let N : int>
+vector<uint, N> reversebits(vector<uint, N> value)
+{
+    VECTOR_MAP_UNARY(uint, N, reversebits, value);
+}
 
 // Round-to-nearest
 __generic<T : __BuiltinFloatingPointType>
@@ -2073,7 +2161,13 @@ matrix<T, N, M> sinh(matrix<T, N, M> x)
 
 // Smooth step (Hermite interpolation)
 __generic<T : __BuiltinFloatingPointType>
-T smoothstep(T min, T max, T x);
+__target_intrinsic(hlsl)
+__target_intrinsic(glsl)
+T smoothstep(T min, T max, T x)
+{
+    let t = saturate((x - min) / (max - min));
+    return t * t * (T(3.0f) - (t + t));
+}
 
 __generic<T : __BuiltinFloatingPointType, let N : int>
 __target_intrinsic(hlsl)
@@ -2113,10 +2207,10 @@ matrix<T, N, M> sqrt(matrix<T, N, M> x)
 __generic<T : __BuiltinFloatingPointType>
 __target_intrinsic(hlsl)
 __target_intrinsic(glsl)
-T step(T y, T x);
-/*{
+T step(T y, T x)
+{
     return x < y ? T(0.0f) : T(1.0f);
-}*/
+}
 
 __generic<T : __BuiltinFloatingPointType, let N : int>
 __target_intrinsic(hlsl)