README.md

Benchmarks

Benchmark suite for Primes.jl, comparing GMP-optimised in-place arithmetic against the generic (allocating) code path for BigInt operations, and measuring end-to-end factorisation performance across different number sizes.

Prerequisites

julia --project=benchmarks -e 'using Pkg; Pkg.instantiate()'

Running

Run all benchmarks:

julia --project=benchmarks benchmarks/run_all.jl

Or run individual suites:

# GMP in-place vs generic (allocating) ECM — the core comparison
julia --project=benchmarks benchmarks/ecm_gmp_vs_generic.jl

# Micro-benchmarks for individual ECM operations
julia --project=benchmarks benchmarks/ecm_microbenchmarks.jl

# End-to-end factor(n) at various sizes
julia --project=benchmarks benchmarks/factorization_endtoend.jl

Benchmark Suites

ecm_gmp_vs_generic.jl

Compares the two ECM code paths for BigInt inputs:

Path	Style	Allocations
ecm_factor(n::BigInt, ...)	In-place GMP (Base.GMP.MPZ.*!)	Near-zero in hot loop
Generic via _ecm_scalar_mul	Functional (new BigInt per op)	O(k) per scalar multiply

Tests at two scales: a ~40-digit and a ~55-digit semiprime.

ecm_microbenchmarks.jl

Benchmarks individual ECM building blocks across three execution modes:

Operation	GMP in-place	Generic BigInt	UInt128 (LLVM)
_mulmod	_mulmod!	_mulmod	_mulmod
_ecm_add	_ecm_add!	_ecm_add	_ecm_add
_ecm_double	_ecm_double!	_ecm_double	_ecm_double
_ecm_scalar_mul	_ecm_scalar_mul!	_ecm_scalar_mul	_ecm_scalar_mul

factorization_endtoend.jl

Benchmarks factor(n) for semiprimes ranging from 12 to 45+ digits, showing how the polyalgorithm (trial division → Pollard rho → ECM → MPQS) scales.