cralgebra

A fast crypto algebra library.

Status

• ✅: complete
• ⚡: partial
• ❌: none

Using the API

The API is split into a few modules:

• types: the algebraic datatypes.
• ops: traits for the different operations.
• algorithms: useful algorithms (e.g., primality testing).
• misc: other things (e.g., random distributions).

Items ending in Dyn or _d require a runtime context, which has a type ending in Context. For example, ModularDyn<T> is used for modular arithmetic, where the modulus is provided at runtime as a ModularContext. Operations on ModularDyn (e.g., add_d) take both this context and the underlying type T's own context. For example:

let modulus: Z2_8 = 17.into();
let inner_ctx = (); // Z2_8 takes no context
let mod_ctx = ModularContext::new(modulus.clone(), &inner_ctx);
let ctx = (mod_ctx, &inner_ctx); // this is how contexts are nested
let a: ModularDyn<Z2_8> = ModularDyn::new_d(4.into(), &ctx);
let b: ModularDyn<Z2_8> = ModularDyn::new_d(15.into(), &ctx);
let r = a.add_d(&b, &ctx);
assert_eq!(r.inner.inner, 2);

Performance

Run this to measure latencies for different operations:

cargo run --example bench --release

This Cargo.toml configuration is recommended for maximum performance:

[profile.release]
opt-level = 3
debug-assertions = false
overflow-checks = false
lto = true
panic = 'unwind'
incremental = false
codegen-units = 1
rpath = false

Further tips:

• Use the most specific type or method for each task.
• Use MontgomeryDyn instead of ModularDyn if doing multiple operations in series, containing multiplications.

Alternative projects

• feanor-math: more featured, with a different approach to API organization.