To get started with Shumai, follow these simple steps: 1. **Install Bun**: Make sure you have Bun installed on your system. You can find the installation instructions on the official [Bun website](https://bun.sh). 2. **Install ArrayFire**: Depending on your OS, install ArrayFire using the appropriate package manager: - For **macOS**: ```bash brew install arrayfire ``` - For **Linux** (Ubuntu): ```bash sudo apt install -y arrayfire-cpu3-dev arrayfire-cpu3-openblas ``` 3. **Install Shumai**: Run the following command to install the Shumai package: ```bash bun install @shumai/shumai ``` 4. **Start Coding**: Import Shumai into your TypeScript or JavaScript project and begin using its powerful tensor operations.

Shumai Frequently Asked Questions:

Q: What platforms are supported by Shumai? A: Shumai is officially supported on macOS and Linux, with additional compatibility for Windows users utilizing Docker and WSL2. Q: How do I set up my environment to use Shumai? A: You must install Bun and ArrayFire first, then install Shumai via Bun. Detailed instructions can be found in the documentation. Q: Can I use Shumai for machine learning applications? A: Yes, Shumai is specifically designed for machine learning and includes features such as differentiable tensors and gradient calculations. Q: Is Shumai suitable for real-time web applications? A: Absolutely! Shumai's efficient computation allows it to be integrated into web applications for fast processing, enhancing user experience. Q: How do I report issues or contribute to Shumai? A: You can file issues directly on the Shumai GitHub repository. If you would like to contribute, please refer to the contribution guidelines provided in the documentation.

Fast Differentiable Tensor Library for JavaScript and TypeScript

Shumai Product Information

What is Shumai?

Shumai by Facebook Research is a fast differentiable tensor library designed specifically for JavaScript and TypeScript developers. This experimental software combines the capabilities of Bun and Flashlight, offering unparalleled performance for those who need efficient computation for their applications. By utilizing native typed arrays, Shumai allows for seamless integration of advanced tensor operations in a familiar JavaScript environment, paving the way for developers and researchers to create robust, high-performance applications.

What are the features of Shumai?

Differentiable Tensors: Shumai supports a wide range of tensor operations, making it an excellent choice for anyone working in fields that require gradient calculations, such as machine learning and deep learning.
Built for Performance: Leveraging the power of Bun and Flashlight, Shumai provides fast FFI (Foreign Function Interface) bindings, ensuring that operations are executed rapidly with performance optimization.
Cross-Platform Support: While Shumai is officially supported on macOS and Linux, users have successfully utilized it on Windows via Docker and WSL2. This flexibility makes Shumai accessible to a broader range of developers.
Integration with ArrayFire: The library is built to harness the capabilities of ArrayFire, allowing users to perform both CPU and GPU computations seamlessly. This ensures that users can benefit from the hardware capabilities available on their systems.
Comprehensive Documentation: Shumai's documentation includes extensive examples and guidelines for usage, helping users to easily integrate it into their projects.

What are the characteristics of Shumai?

Extensible Architecture: Shumai is designed to be easily extendable. Developers can add more functionalities or modify existing behavior to suit their specific needs.
Focus on Speed: With internal optimizations and the use of JIT (Just-In-Time) compilation, Shumai processes tensor operations faster than many existing JavaScript libraries, making it ideal for time-sensitive applications.
Gradient Support: The library includes built-in support for gradient calculations, essential for training machine learning models effectively.
Memory Management: Shumai provides options to manage memory efficiently, helping to reduce overhead from the JavaScript garbage collector and improve performance.
Robust Statistics Logging: Shumai includes a statistics logger that allows developers to monitor performance and optimize their applications effectively.

What are the use cases of Shumai?

Machine Learning: Developers can leverage Shumai’s tensor operations for building and training machine learning models quickly and efficiently in a JavaScript environment.
Data Analysis: With its quick computation capabilities, Shumai is suitable for data manipulation and statistical analysis, enabling researchers to handle large datasets.
Game Development: The library can be utilized in game development for real-time data processing, enhancing the performance of physics simulations and AI behaviors.
Scientific Computing: Shumai’s ability to handle complex mathematical operations makes it a powerful tool for simulations and other computational tasks in scientific research.
Web Applications: Frontend developers can harness Shumai to perform calculations directly in a browser, bringing computational power to interactive web applications.

How to use Shumai?

To get started with Shumai, follow these simple steps:

Install Bun: Make sure you have Bun installed on your system. You can find the installation instructions on the official Bun website.
Install ArrayFire: Depending on your OS, install ArrayFire using the appropriate package manager:
- For macOS:
```
brew install arrayfire
```
- For Linux (Ubuntu):
```
sudo apt install -y arrayfire-cpu3-dev arrayfire-cpu3-openblas
```
Install Shumai: Run the following command to install the Shumai package:
```
bun install @shumai/shumai
```
Start Coding: Import Shumai into your TypeScript or JavaScript project and begin using its powerful tensor operations.

Shumai FAQ

What platforms are supported by Shumai?

How do I set up my environment to use Shumai?

Can I use Shumai for machine learning applications?

Is Shumai suitable for real-time web applications?

How do I report issues or contribute to Shumai?

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