Project Description: The Nexus zkVM

What is the project about?

The Nexus zkVM is a modular, extensible, open-source, and highly-parallelized zero-knowledge virtual machine (zkVM). It's designed for high performance, aiming for a trillion CPU cycles proved per second. It also includes an implementation of folding schemes in the nexus-nova crate.

What problem does it solve?

The project addresses the need for a fast and efficient zkVM that can handle complex computations while maintaining privacy and verifiability. It allows developers to create provable programs, enhancing trust and security in various applications.

What are the features of the project?

Modular and Extensible: Designed to be adaptable and customizable.
Highly-Parallelized: Can leverage significant computing power for speed.
Open-Source: Freely available and encourages community contributions.
Folding Schemes Implementation: Includes nexus-nova crate for folding schemes.
RISC-V Target Support: Compiles and runs on RISC-V architecture.
CLI Tooling: Provides cargo-nexus for easy project creation, running, proving, and verifying.
Rust-Based: Built using the Rust programming language.

What are the technologies used in the project?

Rust: The primary programming language.
RISC-V: The instruction set architecture used for the zkVM.
Zero-Knowledge Proofs: Cryptographic techniques for proving computation correctness without revealing inputs.
Folding Schemes: Implemented in the nexus-nova crate.
CMake: A build system dependency.
Cargo: Rust's package manager and build tool.

What are the benefits of the project?

High Performance: Designed for speed and efficiency.
Enhanced Security and Privacy: Uses zero-knowledge proofs to ensure verifiability without revealing sensitive data.
Open and Collaborative: Open-source nature fosters community involvement and transparency.
Easy to Use: CLI tools simplify development and deployment.
Flexibility: Modular design allows for customization and extension.

What are the use cases of the project?

Provable Computation: Running computations that can be verified by anyone without revealing the underlying data.
Blockchain Applications: Enhancing privacy and scalability of blockchain transactions and smart contracts.
Secure Computation: Performing computations on sensitive data without exposing it.
Verifiable Machine Learning: Proving the integrity of machine learning models and results.
Any application requiring high-performance, verifiable, and privacy-preserving computation.