Scalar Types

JavaScript has no built-in f16, bf16, fp8, or packed-bit numeric model. NumKong handles that with explicit dtype tags and wrapper arrays.

The supported low-precision types and their bit layouts are:

• Float16Array: 1 sign + 5 exponent + 10 mantissa bits, 2 bytes per element, range ±65504, supports Inf and NaN
• BFloat16Array: 1 sign + 8 exponent + 7 mantissa bits, 2 bytes per element, full f32 dynamic range, supports Inf and NaN
• E4M3Array: 1 sign + 4 exponent + 3 mantissa bits, 1 byte per element, range ±448, no Inf, NaN is 0x7F only
• E5M2Array: 1 sign + 5 exponent + 2 mantissa bits, 1 byte per element, range ±57344, supports Inf and NaN
• BinaryArray: packed bits in bytes, 8 elements per byte

Use .byteLength for the exact payload size.

import { Float16Array, E4M3Array, DType, dot, angular } from "numkong";

const a16 = new Float16Array([1, 2, 3]);
const b16 = new Float16Array([4, 5, 6]);
console.log(dot(a16, b16, DType.F16));
console.log(a16.byteLength);

const a8 = new E4M3Array([1, 2, 3]);
const b8 = new E4M3Array([4, 5, 6]);
console.log(angular(a8, b8, DType.E4M3));
console.log(a8.byteLength);

If the underlying storage is a raw Uint16Array or Uint8Array, JS itself cannot know whether those bytes mean integers, f16, bf16, mini-floats, or packed bits. That is exactly when the DType tag becomes mandatory. cast converts many values between all supported types, naming both sides by their dtype string:

numkong.cast(f32Source, "f32", bf16Dest, "bf16");
numkong.cast(f32Source, "f32", e4m3Dest, "e4m3");