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Add floating point matrix multiply-accumulate widening intrinsics
Adds intrinsic support for the FMMLA matrix multiply-add widening instructions introduced by the 2024 dpISA. FEAT_F8F32MM: Neon/SVE2 FP8 to single-precision FEAT_F8F16MM: Neon/SVE2 FP8 to half-precision FEAT_SVE_F16F32MM: SVE half-precision to single-precision
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‎main/acle.md‎

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@@ -466,6 +466,8 @@ Armv8.4-A [[ARMARMv84]](#ARMARMv84). Support is added for the Dot Product intrin
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* Added feature test macro for FEAT_SSVE_FEXPA.
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* Added feature test macro for FEAT_CSSC.
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* Added support for FEAT_FPRCVT intrinsics and `__ARM_FEATURE_FPRCVT`.
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* Added support for modal 8-bit floating point matrix multiply-accumulate widening intrinsics.
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* Added support for 16-bit floating point matrix multiply-accumulate widening intrinsics.
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### References
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associated ACLE intrinsics are available. This implies that
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`__ARM_FEATURE_MATMUL_INT8` and `__ARM_FEATURE_SVE` are both nonzero.
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##### Multiplication of modal 8-bit floating-point matrices
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This section is in
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[**Alpha** state](#current-status-and-anticipated-changes) and might change or be
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extended in the future.
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`__ARM_FEATURE_F8F16MM` is defined to `1` if there is hardware support
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for the NEON and SVE modal 8-bit floating-point matrix multiply-accumulate to half-precision (FEAT_F8F16MM)
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instructions and if the associated ACLE intrinsics are available.
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`__ARM_FEATURE_F8F32MM` is defined to `1` if there is hardware support
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for the NEON and SVE modal 8-bit floating-point matrix multiply-accumulate to single-precision (FEAT_F8F32MM)
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instructions and if the associated ACLE intrinsics are available.
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##### Multiplication of 16-bit floating-point matrices
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`__ARM_FEATURE_SVE_F16F32MM` is defined to `1` if there is hardware support
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for the SVE 16-bit floating-point to 32-bit floating-point matrix multiply and add
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(FEAT_SVE_F16F32MM) instructions and if the associated ACLE intrinsics are available.
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##### Multiplication of 32-bit floating-point matrices
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`__ARM_FEATURE_SVE_MATMUL_FP32` is defined to `1` if there is hardware support
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| [`__ARM_FEATURE_SVE_BITS`](#scalable-vector-extension-sve) | The number of bits in an SVE vector, when known in advance | 256 |
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| [`__ARM_FEATURE_SVE_MATMUL_FP32`](#multiplication-of-32-bit-floating-point-matrices) | 32-bit floating-point matrix multiply extension (FEAT_F32MM) | 1 |
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| [`__ARM_FEATURE_SVE_MATMUL_FP64`](#multiplication-of-64-bit-floating-point-matrices) | 64-bit floating-point matrix multiply extension (FEAT_F64MM) | 1 |
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| [`__ARM_FEATURE_F8F16MM`](#multiplication-of-modal-8-bit-floating-point-matrices) | Modal 8-bit floating-point matrix multiply-accumulate to half-precision extension (FEAT_F8F16MM) | 1 |
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| [`__ARM_FEATURE_F8F32MM`](#multiplication-of-modal-8-bit-floating-point-matrices) | Modal 8-bit floating-point matrix multiply-accumulate to single-precision extension (FEAT_F8F32MM) | 1 |
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| [`__ARM_FEATURE_SVE_F16F32MM`](#multiplication-of-16-bit-floating-point-matrices) | 16-bit floating-point matrix multiply-accumulate to single-precision extension (FEAT_SVE_F16F32MM) | 1 |
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| [`__ARM_FEATURE_SVE_MATMUL_INT8`](#multiplication-of-8-bit-integer-matrices) | SVE support for the integer matrix multiply extension (FEAT_I8MM) | 1 |
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| [`__ARM_FEATURE_SVE_PREDICATE_OPERATORS`](#scalable-vector-extension-sve) | Level of support for C and C++ operators on SVE vector types | 1 |
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| [`__ARM_FEATURE_SVE_VECTOR_OPERATORS`](#scalable-vector-extension-sve) | Level of support for C and C++ operators on SVE predicate types | 1 |
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uint64_t imm_idx);
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```
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### SVE2 floating-point matrix multiply-accumulate instructions.
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#### FMMLA (widening, FP8 to FP16)
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Modal 8-bit floating-point matrix multiply-accumulate to half-precision.
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```c
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// Only if (__ARM_FEATURE_SVE2 && __ARM_FEATURE_F8F16MM)
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svfloat16_t svmmla[_f16_mf8]_fpm(svfloat16_t zda, svmfloat8_t zn, svmfloat8_t zm, fpm_t fpm);
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```
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#### FMMLA (widening, FP8 to FP32)
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Modal 8-bit floating-point matrix multiply-accumulate to single-precision.
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```c
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// Only if (__ARM_FEATURE_SVE2 && __ARM_FEATURE_F8F32MM)
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svfloat32_t svmmla[_f32_mf8]_fpm(svfloat32_t zda, svmfloat8_t zn, svmfloat8_t zm, fpm_t fpm);
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```
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#### FMMLA (widening, FP16 to FP32)
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16-bit floating-point matrix multiply-accumulate to single-precision.
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```c
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// Only if __ARM_FEATURE_SVE_F16F32MM
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svfloat32_t svmmla[_f32_f16](svfloat32_t zda, svfloat16_t zn, svfloat16_t zm);
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```
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### SVE2.1 instruction intrinsics
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The specification for SVE2.1 is in

‎neon_intrinsics/advsimd.md‎

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| <code>float32x4_t <a href="https://developer.arm.com/architectures/instruction-sets/intrinsics/vmlalltbq_laneq_f32_mf8_fpm" target="_blank">vmlalltbq_laneq_f32_mf8_fpm</a>(<br>&nbsp;&nbsp;&nbsp;&nbsp; float32x4_t vd,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t vn,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t vm,<br>&nbsp;&nbsp;&nbsp;&nbsp; const int lane,<br>&nbsp;&nbsp;&nbsp;&nbsp; fpm_t fpm)</code> | `vd -> Vd.4S`<br>`vm -> Vn.16B`<br>`vm -> Vm.B`<br>`0 <= lane <= 15` | `FMLALLBB Vd.4S, Vn.16B, Vm.B[lane]` | `Vd.4S -> result` | `A64` |
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| <code>float32x4_t <a href="https://developer.arm.com/architectures/instruction-sets/intrinsics/vmlallttq_lane_f32_mf8_fpm" target="_blank">vmlallttq_lane_f32_mf8_fpm</a>(<br>&nbsp;&nbsp;&nbsp;&nbsp; float32x4_t vd,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t vn,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x8_t vm,<br>&nbsp;&nbsp;&nbsp;&nbsp; const int lane,<br>&nbsp;&nbsp;&nbsp;&nbsp; fpm_t fpm)</code> | `vd -> Vd.4S`<br>`vm -> Vn.16B`<br>`vm -> Vm.B`<br>`0 <= lane <= 7` | `FMLALLBB Vd.4S, Vn.16B, Vm.B[lane]` | `Vd.4S -> result` | `A64` |
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| <code>float32x4_t <a href="https://developer.arm.com/architectures/instruction-sets/intrinsics/vmlallttq_laneq_f32_mf8_fpm" target="_blank">vmlallttq_laneq_f32_mf8_fpm</a>(<br>&nbsp;&nbsp;&nbsp;&nbsp; float32x4_t vd,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t vn,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t vm,<br>&nbsp;&nbsp;&nbsp;&nbsp; const int lane,<br>&nbsp;&nbsp;&nbsp;&nbsp; fpm_t fpm)</code> | `vd -> Vd.4S`<br>`vm -> Vn.16B`<br>`vm -> Vm.B`<br>`0 <= lane <= 15` | `FMLALLBB Vd.4S, Vn.16B, Vm.B[lane]` | `Vd.4S -> result` | `A64` |
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## Matrix multiplication intrinsics from Armv9.6-A
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### Vector arithmetic
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#### Matrix multiply
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| Intrinsic | Argument preparation | AArch64 Instruction | Result | Supported architectures |
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|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------|-------------------------------|-------------------|---------------------------|
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| <code>float16x4_t <a href="https://developer.arm.com/architectures/instruction-sets/intrinsics/vmmlaq_f16_mf8" target="_blank">vmmlaq_f16_mf8</a>(<br>&nbsp;&nbsp;&nbsp;&nbsp; float16x4_t r,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t a,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t b)</code> | `r -> Vd.4H`<br>`a -> Vn.16B`<br>`b -> Vm.16B` | `FMMLA Vd.4H, Vn.16B, Vm.16B` | `Vd.4H -> result` | `A64` |
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| <code>float32x4_t <a href="https://developer.arm.com/architectures/instruction-sets/intrinsics/vmmlaq_f32_mf8" target="_blank">vmmlaq_f32_mf8</a>(<br>&nbsp;&nbsp;&nbsp;&nbsp; float32x4_t r,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t a,<br>&nbsp;&nbsp;&nbsp;&nbsp; mfloat8x16_t b)</code> | `r -> Vd.4S`<br>`a -> Vn.16B`<br>`b -> Vm.16B` | `FMMLA Vd.4S, Vn.16B, Vm.16B` | `Vd.4S -> result` | `A64` |

‎tools/intrinsic_db/advsimd.csv‎

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float32x4_t vmlalltbq_laneq_f32_mf8_fpm(float32x4_t vd, mfloat8x16_t vn, mfloat8x16_t vm, __builtin_constant_p(lane), fpm_t fpm) vd -> Vd.4S;vm -> Vn.16B; vm -> Vm.B; 0 <= lane <= 15 FMLALLBB Vd.4S, Vn.16B, Vm.B[lane] Vd.4S -> result A64
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float32x4_t vmlallttq_lane_f32_mf8_fpm(float32x4_t vd, mfloat8x16_t vn, mfloat8x8_t vm, __builtin_constant_p(lane), fpm_t fpm) vd -> Vd.4S;vm -> Vn.16B; vm -> Vm.B; 0 <= lane <= 7 FMLALLBB Vd.4S, Vn.16B, Vm.B[lane] Vd.4S -> result A64
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float32x4_t vmlallttq_laneq_f32_mf8_fpm(float32x4_t vd, mfloat8x16_t vn, mfloat8x16_t vm, __builtin_constant_p(lane), fpm_t fpm) vd -> Vd.4S;vm -> Vn.16B; vm -> Vm.B; 0 <= lane <= 15 FMLALLBB Vd.4S, Vn.16B, Vm.B[lane] Vd.4S -> result A64
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<SECTION> Matrix multiplication intrinsics from Armv9.6-A
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float16x4_t vmmlaq_f16_mf8(float16x4_t r, mfloat8x16_t a, mfloat8x16_t b) r -> Vd.4H;a -> Vn.16B;b -> Vm.16B FMMLA Vd.4H, Vn.16B, Vm.16B Vd.4H -> result A64
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float32x4_t vmmlaq_f32_mf8(float32x4_t r, mfloat8x16_t a, mfloat8x16_t b) r -> Vd.4S;a -> Vn.16B;b -> Vm.16B FMMLA Vd.4S, Vn.16B, Vm.16B Vd.4S -> result A64

‎tools/intrinsic_db/advsimd_classification.csv‎

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vmlalltbq_laneq_f32_mf8_fpm Vector arithmetic|Multiply|Multiply-accumulate and widen
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vmlallttq_lane_f32_mf8_fpm Vector arithmetic|Multiply|Multiply-accumulate and widen
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vmlallttq_laneq_f32_mf8_fpm Vector arithmetic|Multiply|Multiply-accumulate and widen
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vmmlaq_f16_mf8 Vector arithmetic|Matrix multiply
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vmmlaq_f32_mf8 Vector arithmetic|Matrix multiply

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