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https://github.com/mekaem/rustops

Exploring operation optimizations in Rust
https://github.com/mekaem/rustops

Last synced: 6 days ago
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Exploring operation optimizations in Rust

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README 

        
# RustOps



This project explores some operation optimizations in Rust, relevant to performance-critical domains like cryptography. The project includes:



1. **Inline Assembly (IFMA)**:

- Requires unsafe code and is platform-specific.

- It is a challenge to achieve this level of optimization safely in Rust.



2. **Compiler Optimizations**:

- Relies on the Rust compiler's ability to optimize.



3. **High-Level Abstractions (SIMD**):

- Uses Rust's `std::arch` module for SIMD operations.

- A balance between performance and safety using high-level abstractions.



4. **Algorithmic Optimizations (Karatsuba)**:

- Implements the Karatsuba algorithm for multiplication.

- Rethinking algorithms can yield performance improvements without low-level optimizations.



5. **External Libraries**:

- Uses the `ed25519-dalek` crate for Ed25519 operations.



## Notes



- IFMA operations only run on supported x86_64 CPUs. Other systems will use a fallback implementation.

- Ed25519 operations work on all systems.



**The text that inspired this (need to remember the author, it's been a while)**:



_"Achieving the same level of optimization as with inline assembly and specific processor instructions like IFMA (Intel's Integer Fused Multiply-Add) instructions directly in Rust without using unsafe code is challenging. The primary reason unsafe is required for such optimizations is that they directly interact with hardware features not abstracted or managed by Rust's safe guarantees. This direct interaction is necessary to leverage specific CPU instructions for performance gains in cryptographic computations or other intensive tasks._



_However, there are some strategies to approach optimizations while adhering to Rust's safety principles, although they might not offer the same performance benefits as using IFMA instructions directly:_



_1. **Rely on Compiler Optimizations**_

- _Modern compilers, including rustc used for Rust, are quite sophisticated and can automatically apply various optimizations at compile time. By writing idiomatic Rust code and enabling higher optimization levels (such as using the release profile), you can allow the compiler to apply optimizations that might include vectorization and other performance improvements where it sees fit._



_2. **Use High-Level Abstractions**_

- _Libraries that abstract over SIMD (Single Instruction, Multiple Data) operations can sometimes offer a way to write more optimized code without directly using unsafe. For example, the `std::arch` module provides access to SIMD operations in a safer manner, though this might still require unsafe blocks for direct SIMD instructions. However, libraries like `rayon` for data parallelism can utilize multicore processors efficiently without requiring unsafe code._



_3. **Leverage External Libraries**_

- _Some cryptographic libraries are optimized at a lower level (in C, C++, or assembly) and provide safe interfaces for Rust. These libraries might already take advantage of specific processor instructions like IFMA for operations where it's beneficial. Using these libraries from Rust can offer the performance benefits of these optimizations while keeping your Rust code safe._



_4. **Algorithmic Optimizations**_

- _Sometimes, rethinking the algorithm or the way computations are performed can yield significant performance improvements without needing to resort to low-level optimizations. Exploring algorithmic changes, pre-computations, or using different mathematical properties can sometimes offset the lack of specific instruction-level optimizations."_