lo/docs/data/simd-sumby.md

name, slug, sourceRef, category, subCategory, similarHelpers, position, signatures

name	slug	sourceRef	category	subCategory	similarHelpers	position	signatures
SumBy	sumby	exp/simd/math.go#L841	exp	simd	exp#simd#sum exp#simd#meanby	20	func SumByInt8[T any, R ~int8](collection []T, iteratee func(item T) R) R func SumByInt16[T any, R ~int16](collection []T, iteratee func(item T) R) R func SumByInt32[T any, R ~int32](collection []T, iteratee func(item T) R) R func SumByInt64[T any, R ~int64](collection []T, iteratee func(item T) R) R func SumByUint8[T any, R ~uint8](collection []T, iteratee func(item T) R) R func SumByUint16[T any, R ~uint16](collection []T, iteratee func(item T) R) R func SumByUint32[T any, R ~uint32](collection []T, iteratee func(item T) R) R func SumByUint64[T any, R ~uint64](collection []T, iteratee func(item T) R) R func SumByFloat32[T any, R ~float32](collection []T, iteratee func(item T) R) R func SumByFloat64[T any, R ~float64](collection []T, iteratee func(item T) R) R func SumByInt8x16[T any, R ~int8](collection []T, iteratee func(item T) R) R func SumByInt8x32[T any, R ~int8](collection []T, iteratee func(item T) R) R func SumByInt8x64[T any, R ~int8](collection []T, iteratee func(item T) R) R func SumByInt16x8[T any, R ~int16](collection []T, iteratee func(item T) R) R func SumByInt16x16[T any, R ~int16](collection []T, iteratee func(item T) R) R func SumByInt16x32[T any, R ~int16](collection []T, iteratee func(item T) R) R func SumByInt32x4[T any, R ~int32](collection []T, iteratee func(item T) R) R func SumByInt32x8[T any, R ~int32](collection []T, iteratee func(item T) R) R func SumByInt32x16[T any, R ~int32](collection []T, iteratee func(item T) R) R func SumByInt64x2[T any, R ~int64](collection []T, iteratee func(item T) R) R func SumByInt64x4[T any, R ~int64](collection []T, iteratee func(item T) R) R func SumByInt64x8[T any, R ~int64](collection []T, iteratee func(item T) R) R func SumByUint8x16[T any, R ~uint8](collection []T, iteratee func(item T) R) R func SumByUint8x32[T any, R ~uint8](collection []T, iteratee func(item T) R) R func SumByUint8x64[T any, R ~uint8](collection []T, iteratee func(item T) R) R func SumByUint16x8[T any, R ~uint16](collection []T, iteratee func(item T) R) R func SumByUint16x16[T any, R ~uint16](collection []T, iteratee func(item T) R) R func SumByUint16x32[T any, R ~uint16](collection []T, iteratee func(item T) R) R func SumByUint32x4[T any, R ~uint32](collection []T, iteratee func(item T) R) R func SumByUint32x8[T any, R ~uint32](collection []T, iteratee func(item T) R) R func SumByUint32x16[T any, R ~uint32](collection []T, iteratee func(item T) R) R func SumByUint64x2[T any, R ~uint64](collection []T, iteratee func(item T) R) R func SumByUint64x4[T any, R ~uint64](collection []T, iteratee func(item T) R) R func SumByUint64x8[T any, R ~uint64](collection []T, iteratee func(item T) R) R func SumByFloat32x4[T any, R ~float32](collection []T, iteratee func(item T) R) R func SumByFloat32x8[T any, R ~float32](collection []T, iteratee func(item T) R) R func SumByFloat32x16[T any, R ~float32](collection []T, iteratee func(item T) R) R func SumByFloat64x2[T any, R ~float64](collection []T, iteratee func(item T) R) R func SumByFloat64x4[T any, R ~float64](collection []T, iteratee func(item T) R) R func SumByFloat64x8[T any, R ~float64](collection []T, iteratee func(item T) R) R

SumBy transforms a collection using an iteratee function and sums the result using SIMD instructions. The automatic dispatch functions (e.g., SumByInt8) will select the best SIMD variant based on CPU capabilities. The specific variants (e.g., SumByInt8x32) use a fixed SIMD instruction set regardless of CPU capabilities.

Requirements

• Go 1.26+ with GOEXPERIMENT=simd
• amd64 architecture only

CPU compatibility

SIMD variant	Lanes	Required flags	Typical CPUs
AVX (xN)	2-16	avx	All amd64
AVX2 (xN)	4-32	avx2	Intel Haswell+, AMD Excavator+
AVX-512 (xN)	8-64	avx512f	Intel Skylake-X+, some Xeons

Note

: The automatic dispatch functions (e.g., SumByInt8) will use the best available SIMD variant for the current CPU. Use specific variants (e.g., SumByInt8x32) only if you know your target CPU supports that instruction set.

type Person struct {
    Name string
    Age  int8
}

people := []Person{
    {Name: "Alice", Age: 25},
    {Name: "Bob", Age: 30},
    {Name: "Charlie", Age: 35},
}

// Automatic dispatch - uses best available SIMD
sum := simd.SumByInt8(people, func(p Person) int8 {
    return p.Age
})
// 90

type Product struct {
    Name  string
    Price float32
    Stock int32
}

products := []Product{
    {Name: "Widget", Price: 10.50, Stock: 5},
    {Name: "Gadget", Price: 20.00, Stock: 3},
    {Name: "Tool", Price: 15.75, Stock: 2},
}

// Sum stock value using specific AVX2 variant
sum := simd.SumByFloat32x8(products, func(p Product) float32 {
    return p.Price * float32(p.Stock)
})
// 152.5

type Metric struct {
    Value uint16
}

metrics := []Metric{
    {Value: 100},
    {Value: 200},
    {Value: 300},
    {Value: 400},
}

// Using AVX variant - works on all amd64
sum := simd.SumByUint16x8(metrics, func(m Metric) uint16 {
    return m.Value
})
// 1000

// Empty collection returns 0
type Item struct {
    Count int64
}

sum := simd.SumByInt64([]Item{}, func(i Item) int64 {
    return i.Count
})
// 0