The Decentralized Science Computational Network (DeSci + DePIN)

OpenSciNet is a peer-to-peer infrastructure designed to democratize high-performance computing (HPC) for scientific advancement. By leveraging underutilized global compute resources, we provide a transparent, verifiable, and scalable fabric for researchers in AI, Biology, and Physics.

Website | Twitter | YouTube | Whitepaper (Coming Soon)

Scientific progress is currently bottlenecked by the high cost and centralized nature of compute clusters. OpenSciNet breaks these silos by allowing anyone to contribute GPU/CPU power to a global "Neural Mesh", earning rewards while accelerating breakthroughs in:

• Artificial Intelligence: Large-scale model training and inference.
• Bio-Data: Genomic sequencing and protein folding.
• Physics: Complex climate simulations and particle modeling.

OpenSciNet is built on three core pillars: Distributed Node Fabric: A lightweight, containerized client (Docker-based) for seamless node participation. ZK-Verification Layer: Zero-Knowledge proofs to ensure compute integrity without compromising data privacy. Smart Orchestration: An automated scheduler that matches research tasks to the most efficient available nodes.

• Phase 1: Genesis - Protocol architecture and core whitepaper. (Current)
• Phase 2: Alpha Mesh - Private testnet for invited node operators.
• Phase 3: Open Discovery - Public incentivized testnet launch.
• Phase 4: Mainnet - Full DAO governance and global compute marketplace.

We are currently in Stealth Development.

For Developers We are looking for contributors experienced in:

• Rust / Go (Protocol Level)
• CUDA / OpenCL (Compute Optimization)
• libp2p (Networking)

For Node Operators

Hardware requirements will be released soon. Generally, we will support:

• Tier 1: High-end NVIDIA GPUs (A100/H100 equivalents)
• Tier 2: Consumer GPUs (RTX 30/40 series)
• Tier 3: CPU-only research validation nodes

This project is licensed under the Business Source License 1.1 - see the LICENSE file for details.

"Advancing science at the speed of the mesh"