Add a tutorial on GPU for classical attacks

[wsxrdv]

Add a tutorial for JAX powered CPA and template attacks.

[gemini-code-assist]

Summary of Changes

Hello @wsxrdv, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new tutorial that delves into optimizing classical side-channel analysis techniques, specifically Correlation Power Analysis (CPA) and Template Attacks, by leveraging JAX for GPU acceleration. The tutorial provides practical examples and in-depth explanations of how JAX's features, such as JIT compilation, vmap, and lax.scan, can significantly enhance performance. It also covers the computational model of GPUs, memory transfer considerations, and the benefits of batching data for efficient processing, aiming to equip users with the knowledge to implement and optimize their own side-channel attack methods.

Highlights

• New GPU Tutorial: A comprehensive tutorial on optimizing classical side-channel attacks (CPA and Template attacks) using JAX for GPU acceleration has been added.
• JAX-powered CPA Implementation: New Python code for Correlation Power Analysis (CPA) is introduced, demonstrating both single-byte and multi-byte index attacks with JAX's batching and vectorization capabilities.
• JAX-powered Template Attack Implementation: New Python code for Template Attacks is added, featuring online template profiling and attack phases, optimized with JAX.
• Batched SNR Computation: The tutorial revisits Signal-to-Noise Ratio (SNR) computation, showcasing performance improvements through JAX's batched processing.
• Website Navigation Update: The website's navigation has been updated to include the new "GPU Acceleration of CPA and Template Attacks" tutorial under a new "Classical Attacks" category.

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[gemini-code-assist]

Code Review

This pull request introduces a comprehensive tutorial on accelerating classical side-channel attacks (CPA and Template attacks) using JAX for GPU computation. The changes include new Python scripts for the attacks and a detailed markdown file for the tutorial. My review focuses on improving code correctness, maintainability, and clarity. I've identified a critical bug in the template attack implementation and a few issues in the tutorial's code snippets. Additionally, I've provided suggestions to correct type hints, docstrings, and other parts of the code to enhance the quality and readability of the examples.