torchlet

A lightweight torch like tensor computation library implemented from scratch in C and CUDA.

I created this to better understand the inner workings of tensor libraries like PyTorch, making it an excellent resource for learning how these libraries work under the hood.

Features

• Basic tensor operations implemented in C and CUDA
• Simple and readable implementation focused on learning
• GPU acceleration support through CUDA
• Zero external dependencies
• Clear code structure for educational purposes

Prerequisites

• C compiler (gcc/clang)
• CUDA Toolkit
• Make

Getting Started

Basic Usage

Here's a simple example demonstrating matrix multiplication with torchlet:

// main.cu
#include "tensor.h"

int main() {
    // Create two random tensors
    Tensor *a = tensor_randn((size_t[]){4, 5}, 2);  // 4x5 matrix
    Tensor *b = tensor_randn((size_t[]){5, 3}, 2);  // 5x3 matrix
    
    // Perform matrix multiplication
    Tensor *c = tensor_matmul(a, b);  // Results in a 4x3 matrix
    
    // Display results
    tensor_print(c);   // Print tensor values
    tensor_debug(c);   // Print tensor metadata
    
    // Clean up
    tensor_free(a);
    tensor_free(b);
    tensor_free(c);
    
    return 0;
}

Compiling Your Code

nvcc -arch=sm_86 -lm tensor.c tensor.cu main.cu -o main

Running the Example

./main

Contributing

Contributions are welcome! If you find a bug, have an idea for an enhancement, or want to contribute in any way, feel free to open an issue or submit a pull request.

License

This project is licensed under the AGPL3 License. For details, see the LICENSE file.