Skip to content

Future Roadmap: Performance & Multi-threading (Python vs Rust)

This document addresses current Python performance issues and HieraChain's future technology direction.

The Pure Python Problem

HieraChain is designed with a future-oriented architecture to leverage parallel processing. However, we face reality:

  • Python GIL (Global Interpreter Lock): Current Python versions are still limited by the GIL, making multi-core CPU utilization suboptimal for CPU-bound tasks like Blockchain Consensus.
  • Python 3.14+ (Free-threading): Although Python 3.13/3.14 has begun supporting "no-GIL" (Free-threading), it is not yet stable enough for Production in critical financial/data systems.

=> Consequence: If you run HieraChain in "Pure Python" mode, performance will be significantly limited under high load.

High-Performance Solution (Rust Acceleration)

To solve the performance problem immediately without waiting for Python's Free-threading to mature, we provide alternatives based on the Rust language:

Self-Managed Integration

You can use the Consensus library written in Rust:

  • Repository: https://github.com/VanDung-dev/HieraChain-Consensus
  • Description: A high-performance Consensus library using PyO3 to communicate with Python.
  • Note: You will need to MANUALLY CONFIGURE and modify code to integrate this library into the current HieraChain.

hrc-core (Enterprise / Lazy Mode)

  • What is hrc-core?: This is the HieraChain kernel written in pure Rust (Native Rust) while maintaining a Python interface (Python Bindings) for ease of use. It delivers maximum Rust performance with Python convenience.
  • Status: Currently hrc-core is in testing and refinement phase.

This document is intended to guide Developers who want to optimize HieraChain performance beyond current Python limitations.