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ac8295b68a
* style(simd): rename sse to avx * fix(exp,simd): apply the right avx512 constraints to a few methods * fix(exp,simd): apply the right avx512 constraints to a few methods
84 lines
3.0 KiB
Markdown
84 lines
3.0 KiB
Markdown
---
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name: Mean
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slug: mean
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sourceRef: exp/simd/math_avx.go#L352
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category: exp
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subCategory: simd
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similarHelpers:
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- exp#simd#mean
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- exp#simd#meanby
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position: 10
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signatures:
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- "func MeanInt8x16[T ~int8](collection []T) T"
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- "func MeanInt8x32[T ~int8](collection []T) T"
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- "func MeanInt8x64[T ~int8](collection []T) T"
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- "func MeanInt16x8[T ~int16](collection []T) T"
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- "func MeanInt16x16[T ~int16](collection []T) T"
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- "func MeanInt16x32[T ~int16](collection []T) T"
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- "func MeanInt32x4[T ~int32](collection []T) T"
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- "func MeanInt32x8[T ~int32](collection []T) T"
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- "func MeanInt32x16[T ~int32](collection []T) T"
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- "func MeanInt64x2[T ~int64](collection []T) T"
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- "func MeanInt64x4[T ~int64](collection []T) T"
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- "func MeanInt64x8[T ~int64](collection []T) T"
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- "func MeanUint8x16[T ~uint8](collection []T) T"
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- "func MeanUint8x32[T ~uint8](collection []T) T"
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- "func MeanUint8x64[T ~uint8](collection []T) T"
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- "func MeanUint16x8[T ~uint16](collection []T) T"
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- "func MeanUint16x16[T ~uint16](collection []T) T"
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- "func MeanUint16x32[T ~uint16](collection []T) T"
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- "func MeanUint32x4[T ~uint32](collection []T) T"
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- "func MeanUint32x8[T ~uint32](collection []T) T"
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- "func MeanUint32x16[T ~uint32](collection []T) T"
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- "func MeanUint64x2[T ~uint64](collection []T) T"
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- "func MeanUint64x4[T ~uint64](collection []T) T"
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- "func MeanUint64x8[T ~uint64](collection []T) T"
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- "func MeanFloat32x4[T ~float32](collection []T) T"
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- "func MeanFloat32x8[T ~float32](collection []T) T"
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- "func MeanFloat32x16[T ~float32](collection []T) T"
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- "func MeanFloat64x2[T ~float64](collection []T) T"
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- "func MeanFloat64x4[T ~float64](collection []T) T"
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- "func MeanFloat64x8[T ~float64](collection []T) T"
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---
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Calculates the arithmetic mean of a collection using SIMD instructions. The suffix (x2, x4, x8, x16, x32, x64) indicates the number of lanes processed simultaneously.
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## Requirements
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- **Go 1.26+** with `GOEXPERIMENT=simd`
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- **amd64** architecture only
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### CPU compatibility
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| SIMD variant | Lanes | Required flags | Typical CPUs |
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| ------------ | ----- | -------------- | ------------------------------ |
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| AVX (xN) | 2-16 | `avx` | All amd64 |
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| AVX2 (xN) | 4-32 | `avx2` | Intel Haswell+, AMD Excavator+ |
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| AVX-512 (xN) | 8-64 | `avx512f` | Intel Skylake-X+, some Xeons |
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> **Note**: Choose the variant matching your CPU's capabilities. Higher lane counts provide better performance but require newer CPU support.
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```go
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// Using AVX2 variant (32 lanes at once) - Intel Haswell+ / AMD Excavator+
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mean := simd.MeanInt8x32([]int8{1, 2, 3, 4, 5})
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// 3
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```
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```go
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// Using AVX-512 variant (16 lanes at once) - Intel Skylake-X+
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mean := simd.MeanFloat32x16([]float32{1.0, 2.0, 3.0, 4.0})
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// 2.5
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```
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```go
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// Using AVX variant (8 lanes at once) - works on all amd64
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mean := simd.MeanInt16x8([]int16{10, 20, 30, 40})
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// 25
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```
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```go
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// Empty collection returns 0
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mean := simd.MeanUint32x4([]uint32{})
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// 0
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```
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