Marlin

Welcome to Marlin! This repository is dedicated to exploring and experimenting with Rust-based solutions for deep learning inferencing. Our goal is to leverage Rust's performance and safety features to improve the efficiency of serving large deep learning models.

Overview

Marlin is an experimental project focused on evaluating Rust's capabilities in handling deep learning inference tasks. We compare Rust-based implementations with Python counterparts to assess performance, latency, and scalability.

Features

• Rust-based Inference: Implementation of deep learning models using Rust, with emphasis on performance and thread safety.
• Model Serving: Use of Candle from Hugging Face and actix-web for serving models.
• Benchmarking: Tools and scripts for performance and encoding time benchmarks.
• Comparative Analysis: Side-by-side comparison with Python-based implementations to evaluate performance differences.

Getting Started

Prerequisites

• Rust (1.67.0 or later)
• cargo (Rust package manager and build tool)

Installation

1. Clone the repository:

   git clone https://github.com/AbhishekBose/marlin.git
   cd marlin
   

2. Build the project:

   cargo build
   

Running the Project

1. Start the Rust-based server:

   cargo run --release
   

2. Run the Python-based server (if applicable):

   cd scripts
   pip fastapi uvicorn sentence-transformers
   uvicorn main:app --reload
   

3. Perform Load and Encoding Benchmarks:

   • Use the provided benchmarking scripts in the scripts/ directory to test performance and compare results.

Contributing

Contributions are welcome! Please open an issue or submit a pull request if you have suggestions, improvements, or bug fixes.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any questions or discussions, feel free to reach out to Abhishek Bose.

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Happy experimenting! 🚀