tandem rng

using Pkg; Pkg.add(url="https://github.com/tandem-rng/TandemRNG.jl")
using TandemRNG
rng = Tandem8x32(42)
x, rng = rand_next(rng, Float64)    # value and next generator

$ git clone https://github.com/tandem-rng/tandem-c && make -C tandem-c
#include "tandem.h"
tandem_rng rng = tandem_seed(42, 0, 0);
double x = tandem_next_f64(&rng);

$ cargo add tandem-rng --git https://github.com/tandem-rng/tandem-rs
let mut rng = tandem_rng::Tandem::new(42);
let x = rng.next_f64();
let worker = rng.split(7);          // by index, from the key

$ pip install git+https://github.com/tandem-rng/tandem-numpy
from tandem_rng import TandemGenerator
g = TandemGenerator(42)
z = g.standard_normal(10**6)

$ git clone https://github.com/tandem-rng/tandem-cuda
#include "tandem.cuh"
auto g = tandem::generator::seed(42);
g.fill_f64(x, n);                   // x in device memory

$ pip install git+https://github.com/tandem-rng/tandem-jax
import jax, tandem_jax as tj
key = tj.key(42)
z = jax.random.normal(key, (1000,)) # any jax.random function

remotes::install_github("tandem-rng/tandem-r")
library(tandemrng)
rng <- tandem(42)
u <- tandem_runif(rng, 1e6)

$ pip install --no-build-isolation git+https://github.com/tandem-rng/tandem-torch
from tandem_torch import Tandem
t = Tandem(42)
z = t.randn(1000)                   # also device="cuda"

$ npm install github:tandem-rng/tandem-webgpu
import { seed, Tandem } from "tandem-webgpu";
const rng = new Tandem(seed(42n));
const xs = rng.fillF64(1 << 20);

! fpm.toml: tandem_rng = { git = "https://github.com/tandem-rng/tandem-fortran" }
use tandem_rng
rng = tandem_new(42_int64)
x = rng%next_real64()

$ git clone --recurse-submodules https://github.com/tandem-rng/tandem-kokkos
#include <tandem/kokkos.hpp>
tandem::Rng rng(42);
tandem::fill(x, rng);               // any contiguous View

$ git clone https://github.com/tandem-rng/tandem-java && mvn -f tandem-java install
Tandem rng = Tandem.seed(42);
double x = rng.nextDouble();
Tandem worker = rng.split(7);

$ git clone https://github.com/tandem-rng/tandem-mojo && cd tandem-mojo && pixi install
from tandem import Tandem
var rng = Tandem(42)
var x = rng.next_f64()

$ git clone --recurse-submodules https://github.com/tandem-rng/tandem-sycl
#include <tandem/sycl.hpp>
tandem::Rng rng(42);
tandem::fill(q, x, n, rng);         // USM memory on queue q

// Package.swift: .package(url: "https://github.com/tandem-rng/tandem-metal", branch: "main")
import Tandem
var rng = Tandem(seed: 42)
let x = rng.nextF64()               // GPU fills take a Metal buffer

$ pip install git+https://github.com/tandem-rng/tandem-mlx
import mlx.core as mx, tandem_mlx as tm
key = tm.key(42)
z = tm.normal(key, (1000,))         # Metal kernel on the GPU

-- cabal.project: source-repository-package, location: https://github.com/tandem-rng/tandem-hs
import System.Random.Tandem qualified as T
let g0 = T.seed 42
    (x, g1) = T.nextDouble g0       -- value and next generator

$ git clone https://github.com/tandem-rng/tandem-ml && cd tandem-ml && opam install . && dune build
let g = Tandem.seed 42
let x, g = Tandem.float g
let worker = Tandem.split g 7       (* by index, from the key *)