bmb-compute

High-performance compute functions powered by BMB — Node.js FFI bindings.

Installation

npm install bmb-compute koffi

Requires the bmb_compute native shared library. See Getting the native library.

Getting the native library

Option A — Download from GitHub Releases (recommended):

1. Go to lang-bmb Releases
2. Download bmb-libs-<your-platform>.zip from the latest release
3. Place bmb_compute.dll / libbmb_compute.so / libbmb_compute.dylib next to index.js

Option B — Build from source:

cd /path/to/lang-bmb
cargo build --release
./target/release/bmb build ecosystem/bmb-compute/src/lib.bmb --shared -o ecosystem/bmb-compute/bmb_compute

Functions

| Function | Description | |----------|-------------| | abs(n) | Absolute value | | min(a, b) | Minimum | | max(a, b) | Maximum | | clamp(n, lo, hi) | Clamp to range | | sign(n) | Sign (-1/0/1) | | ipow(base, exp) | Integer power | | isqrt(n) | Integer square root | | factorial(n) | Factorial | | rand_next(seed) | XorShift64* next value | | rand_u64(seed) | Uniform u64 | | rand_range(seed, lo, hi) | Random in range | | sum(arr) | Array sum (scaled ×1000) | | mean(arr) | Mean (scaled ×1000) | | variance(arr) | Variance (scaled ×1000) | | median(arr) | Median (scaled ×1000) | | dot_product(a, b) | Dot product | | dist_squared(a, b) | Squared distance | | weighted_sum(vals, weights) | Weighted sum (scaled) | | vec_sum(arr) | Vector sum | | vec_max(arr) | Vector maximum | | vec_min(arr) | Vector minimum | | vec_count_positive(arr) | Count positive elements | | vec_count_negative(arr) | Count negative elements | | vec_count_zero(arr) | Count zero elements | | vec_range(arr) | max - min | | vec_argmax(arr) | Index of maximum | | vec_argmin(arr) | Index of minimum |

License

MIT