Add mul_add_relaxed methods for floating-point types

compiler/rustc_span/src/symbol.rs

@@ -1089,6 +1089,7 @@ symbols! {
         file_options,
         flags,
         float,
+        float_mul_add_relaxed,
         float_to_int_unchecked,
         floorf16,
         floorf32,

library/core/src/num/f128.rs

@@ -1449,6 +1449,59 @@ impl f128 {
     pub const fn algebraic_rem(self, rhs: f128) -> f128 {
         intrinsics::frem_algebraic(self, rhs)
     }
+
+    /// Fused multiply-add with relaxed precision semantics. Computes `(self * a) + b`,
+    /// non-deterministically executing either a fused multiply-add (one rounding) or
+    /// two separate operations with intermediate rounding.
+    ///
+    /// The operation may be fused if the code generator determines that the target
+    /// instruction set has support for a fused operation and that it is more efficient
+    /// than separate multiply and add instructions. Whether fusion occurs is unspecified
+    /// and may depend on optimization level and context.
+    ///
+    /// # Precision
+    ///
+    /// Unlike [`mul_add`](Self::mul_add), this operation does not guarantee which
+    /// rounding behavior will occur. It may perform either:
+    /// - A fused multiply-add with one rounding (more accurate)
+    /// - Separate multiply and add operations with two roundings (less accurate)
+    ///
+    /// Use this method when you need performance optimization but can tolerate
+    /// non-deterministic precision. If you require guaranteed precision, use
+    /// [`mul_add`](Self::mul_add) (guaranteed one rounding) or the separate
+    /// multiply and add operations (guaranteed two roundings).
+    ///
+    /// If you want even more optimization opportunities and aren't concerned about
+    /// error bounds, consider using the algebraic operations such as
+    /// [`algebraic_mul`](Self::algebraic_mul) and [`algebraic_add`](Self::algebraic_add).
+    ///
+    /// # Examples
+    ///
+    /// ```ignore (f128 support is platform-specific)
+    /// #![feature(f128)]
+    /// #![feature(float_mul_add_relaxed)]
+    /// # #[cfg(reliable_f128)] {
+    ///
+    /// let m = 10.0_f128;
+    /// let x = 4.0_f128;
+    /// let b = 60.0_f128;
+    ///
+    /// // The result may be computed as either:
+    /// // - (m * x) + b with fused rounding, or
+    /// // - (m * x) + b with separate roundings
+    /// let result = m.mul_add_relaxed(x, b);
+    ///
+    /// // For simple values, both approaches give the same result
+    /// assert_eq!(result, 100.0);
+    /// # }
+    /// ```
+    #[must_use = "method returns a new number and does not mutate the original value"]
+    #[unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[rustc_const_unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[inline]
+    pub const fn mul_add_relaxed(self, a: f128, b: f128) -> f128 {
+        intrinsics::fmuladdf128(self, a, b)
+    }
 }
 
 // Functions in this module fall into `core_float_math`

library/core/src/num/f16.rs

@@ -1434,6 +1434,59 @@ impl f16 {
     pub const fn algebraic_rem(self, rhs: f16) -> f16 {
         intrinsics::frem_algebraic(self, rhs)
     }
+
+    /// Fused multiply-add with relaxed precision semantics. Computes `(self * a) + b`,
+    /// non-deterministically executing either a fused multiply-add (one rounding) or
+    /// two separate operations with intermediate rounding.
+    ///
+    /// The operation may be fused if the code generator determines that the target
+    /// instruction set has support for a fused operation and that it is more efficient
+    /// than separate multiply and add instructions. Whether fusion occurs is unspecified
+    /// and may depend on optimization level and context.
+    ///
+    /// # Precision
+    ///
+    /// Unlike [`mul_add`](Self::mul_add), this operation does not guarantee which
+    /// rounding behavior will occur. It may perform either:
+    /// - A fused multiply-add with one rounding (more accurate)
+    /// - Separate multiply and add operations with two roundings (less accurate)
+    ///
+    /// Use this method when you need performance optimization but can tolerate
+    /// non-deterministic precision. If you require guaranteed precision, use
+    /// [`mul_add`](Self::mul_add) (guaranteed one rounding) or the separate
+    /// multiply and add operations (guaranteed two roundings).
+    ///
+    /// If you want even more optimization opportunities and aren't concerned about
+    /// error bounds, consider using the algebraic operations such as
+    /// [`algebraic_mul`](Self::algebraic_mul) and [`algebraic_add`](Self::algebraic_add).
+    ///
+    /// # Examples
+    ///
+    /// ```ignore (f16 support is platform-specific)
+    /// #![feature(f16)]
+    /// #![feature(float_mul_add_relaxed)]
+    /// # #[cfg(reliable_f16)] {
+    ///
+    /// let m = 10.0_f16;
+    /// let x = 4.0_f16;
+    /// let b = 60.0_f16;
+    ///
+    /// // The result may be computed as either:
+    /// // - (m * x) + b with fused rounding, or
+    /// // - (m * x) + b with separate roundings
+    /// let result = m.mul_add_relaxed(x, b);
+    ///
+    /// // For simple values, both approaches give the same result
+    /// assert_eq!(result, 100.0);
+    /// # }
+    /// ```
+    #[must_use = "method returns a new number and does not mutate the original value"]
+    #[unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[rustc_const_unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[inline]
+    pub const fn mul_add_relaxed(self, a: f16, b: f16) -> f16 {
+        intrinsics::fmuladdf16(self, a, b)
+    }
 }
 
 // Functions in this module fall into `core_float_math`

library/core/src/num/f32.rs

@@ -1612,6 +1612,56 @@ impl f32 {
     pub const fn algebraic_rem(self, rhs: f32) -> f32 {
         intrinsics::frem_algebraic(self, rhs)
     }
+
+    /// Fused multiply-add with relaxed precision semantics. Computes `(self * a) + b`,
+    /// non-deterministically executing either a fused multiply-add (one rounding) or
+    /// two separate operations with intermediate rounding.
+    ///
+    /// The operation may be fused if the code generator determines that the target
+    /// instruction set has support for a fused operation and that it is more efficient
+    /// than separate multiply and add instructions. Whether fusion occurs is unspecified
+    /// and may depend on optimization level and context.
+    ///
+    /// # Precision
+    ///
+    /// Unlike [`mul_add`](Self::mul_add), this operation does not guarantee which
+    /// rounding behavior will occur. It may perform either:
+    /// - A fused multiply-add with one rounding (more accurate)
+    /// - Separate multiply and add operations with two roundings (less accurate)
+    ///
+    /// Use this method when you need performance optimization but can tolerate
+    /// non-deterministic precision. If you require guaranteed precision, use
+    /// [`mul_add`](Self::mul_add) (guaranteed one rounding) or the separate
+    /// multiply and add operations (guaranteed two roundings).
+    ///
+    /// If you want even more optimization opportunities and aren't concerned about
+    /// error bounds, consider using the algebraic operations such as
+    /// [`algebraic_mul`](Self::algebraic_mul) and [`algebraic_add`](Self::algebraic_add).
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// #![feature(float_mul_add_relaxed)]
+    ///
+    /// let m = 10.0_f32;
+    /// let x = 4.0_f32;
+    /// let b = 60.0_f32;
+    ///
+    /// // The result may be computed as either:
+    /// // - (m * x) + b with fused rounding, or
+    /// // - (m * x) + b with separate roundings
+    /// let result = m.mul_add_relaxed(x, b);
+    ///
+    /// // For simple values, both approaches give the same result
+    /// assert_eq!(result, 100.0);
+    /// ```
+    #[must_use = "method returns a new number and does not mutate the original value"]
+    #[unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[rustc_const_unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[inline]
+    pub const fn mul_add_relaxed(self, a: f32, b: f32) -> f32 {
+        intrinsics::fmuladdf32(self, a, b)
+    }
 }
 
 /// Experimental implementations of floating point functions in `core`.

library/core/src/num/f64.rs

@@ -1610,6 +1610,56 @@ impl f64 {
     pub const fn algebraic_rem(self, rhs: f64) -> f64 {
         intrinsics::frem_algebraic(self, rhs)
     }
+
+    /// Fused multiply-add with relaxed precision semantics. Computes `(self * a) + b`,
+    /// non-deterministically executing either a fused multiply-add (one rounding) or
+    /// two separate operations with intermediate rounding.
+    ///
+    /// The operation may be fused if the code generator determines that the target
+    /// instruction set has support for a fused operation and that it is more efficient
+    /// than separate multiply and add instructions. Whether fusion occurs is unspecified
+    /// and may depend on optimization level and context.
+    ///
+    /// # Precision
+    ///
+    /// Unlike [`mul_add`](Self::mul_add), this operation does not guarantee which
+    /// rounding behavior will occur. It may perform either:
+    /// - A fused multiply-add with one rounding (more accurate)
+    /// - Separate multiply and add operations with two roundings (less accurate)
+    ///
+    /// Use this method when you need performance optimization but can tolerate
+    /// non-deterministic precision. If you require guaranteed precision, use
+    /// [`mul_add`](Self::mul_add) (guaranteed one rounding) or the separate
+    /// multiply and add operations (guaranteed two roundings).
+    ///
+    /// If you want even more optimization opportunities and aren't concerned about
+    /// error bounds, consider using the algebraic operations such as
+    /// [`algebraic_mul`](Self::algebraic_mul) and [`algebraic_add`](Self::algebraic_add).
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// #![feature(float_mul_add_relaxed)]
+    ///
+    /// let m = 10.0_f64;
+    /// let x = 4.0_f64;
+    /// let b = 60.0_f64;
+    ///
+    /// // The result may be computed as either:
+    /// // - (m * x) + b with fused rounding, or
+    /// // - (m * x) + b with separate roundings
+    /// let result = m.mul_add_relaxed(x, b);
+    ///
+    /// // For simple values, both approaches give the same result
+    /// assert_eq!(result, 100.0);
+    /// ```
+    #[must_use = "method returns a new number and does not mutate the original value"]
+    #[unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[rustc_const_unstable(feature = "float_mul_add_relaxed", issue = "151770")]
+    #[inline]
+    pub const fn mul_add_relaxed(self, a: f64, b: f64) -> f64 {
+        intrinsics::fmuladdf64(self, a, b)
+    }
 }
 
 #[unstable(feature = "core_float_math", issue = "137578")]

tests/ui/intrinsics/float-mul-add-relaxed.rs

@@ -0,0 +1,49 @@
+//@ run-pass
+//@ compile-flags: -O
+
+#![feature(float_mul_add_relaxed)]
+
+fn main() {
+    test_f32();
+    test_f64();
+}
+
+fn test_f32() {
+    let a = 2.0_f32;
+    let b = 3.0_f32;
+    let c = 4.0_f32;
+
+    let result = a.mul_add_relaxed(b, c);
+    assert_eq!(result, 10.0);
+
+    // Test with values where precision matters less
+    let x = 1.0_f32;
+    let y = 1.0_f32;
+    let z = 1.0_f32;
+    assert_eq!(x.mul_add_relaxed(y, z), 2.0);
+
+    // Test edge cases
+    assert!(f32::NAN.mul_add_relaxed(1.0, 1.0).is_nan());
+    assert_eq!(f32::INFINITY.mul_add_relaxed(2.0, 1.0), f32::INFINITY);
+    assert_eq!(0.0_f32.mul_add_relaxed(f32::INFINITY, 1.0), 1.0);
+}
+
+fn test_f64() {
+    let a = 2.0_f64;
+    let b = 3.0_f64;
+    let c = 4.0_f64;
+
+    let result = a.mul_add_relaxed(b, c);
+    assert_eq!(result, 10.0);
+
+    // Test with values where precision matters less
+    let x = 1.0_f64;
+    let y = 1.0_f64;
+    let z = 1.0_f64;
+    assert_eq!(x.mul_add_relaxed(y, z), 2.0);
+
+    // Test edge cases
+    assert!(f64::NAN.mul_add_relaxed(1.0, 1.0).is_nan());
+    assert_eq!(f64::INFINITY.mul_add_relaxed(2.0, 1.0), f64::INFINITY);
+    assert_eq!(0.0_f64.mul_add_relaxed(f64::INFINITY, 1.0), 1.0);
+}