🏗️ Arxis Core Architecture

Overview

Arxis Core is an ecosystem of over 120 Rust packages organized into a modular architecture with three main layers:

Design Principles

1. Modularity

Each package has a single, well-defined responsibility. Dependencies are explicit and minimized.

# Example of minimal dependencies
[dependencies]
avx-error = { path = "../avx-error" }
avx-std = { path = "../avx-std", optional = true }

2. Zero-Cost Abstractions

Arxis Core abstractions impose no runtime costs. Code is optimized at compile time.

// Generic abstraction with no overhead
pub trait Processor {
    fn process(&self, data: T) -> Result;
}

// Monomorphized at compile-time
impl Processor for MyProcessor {
    #[inline]
    fn process(&self, data: u32) -> Result {
        Ok(data * 2)
    }
}

3. Safety-First

Memory safety guaranteed by Rust's type system. Minimal use of unsafe, always documented.

4. Async-Native

Native support for asynchronous operations using Tokio as the primary runtime.

5. Platform-Agnostic

Support for multiple platforms: Linux, Windows, macOS, WebAssembly.

Architecture Layers

Infrastructure Layer

Provides fundamental building blocks:

• avx-std: Extensões da biblioteca padrão
• avx-error: Sistema de erros unificado
• avx-alloc: Alocadores de memória customizados
• avx-sync: Primitivos de sincronização
• avx-time: Manipulação de tempo e duração
• avx-id: Geração de identificadores únicos

Domain Layer

Specialized workspaces for different domains:

• AI/ML: Tensors, neural networks, distributed training
• GIS: Geometry, projections, spatial analysis
• Network: Protocols, servers, clients
• Database: Storage, indexing, queries

Application Layer

Complete services built on top of lower layers:

• Analytics Server: Real-time data processing
• Documentation Site: Documentation system
• Examples: Demonstration applications

Core Workspace

The main workspace contains the fundamental packages:

[workspace]
members = [
    "avx-std",
    "avx-error",
    "avx-sync",
    "avx-alloc",
    "avx-buffer",
    "avx-time",
    "avx-id",
    "avx-primitives",
    "avx-meta",
    "avx-nucleus",
]

resolver = "2"

[workspace.dependencies]
tokio = { version = "1.35", features = ["full"] }
serde = { version = "1.0", features = ["derive"] }
thiserror = "1.0"

Features

• Shared dependencies at workspace level
• Optimized incremental compilation
• Synchronized versioning
• Integrated tests

AI Workspace

Specialized workspace for artificial intelligence and machine learning:

Structure

avx-ai-workspace/
├── avxdb-core/          # Banco de dados vetorial
├── avx-quinn/           # QUIC protocol
├── avx-tensor/          # Operações com tensores
├── avx-neural/          # Redes neurais
├── avx-training/        # Treinamento distribuído
└── avx-inference/       # Inferência otimizada

Key Features

• GPU support via CUDA and ROCm
• Vectorized operations (SIMD)
• Distributed training
• Optimized graph computation
• Quantization and pruning

Geo Workspace

Complete system for geospatial data:

Components

• avx-geometry: Primitivos geométricos
• avx-projection: Sistemas de coordenadas
• avx-spatial: Índices espaciais (R-tree, Quadtree)
• avx-gis: Análise GIS de alto nível
• avx-raster: Processamento de imagens raster

Data Flow

// GIS processing pipeline
use avx_gis::{Point, Polygon, SpatialIndex};

let index = SpatialIndex::new();
let polygon = Polygon::from_wkt("POLYGON((0 0, 1 0, 1 1, 0 1, 0 0))")?;
index.insert(polygon);

let query_point = Point::new(0.5, 0.5);
let results = index.query_within_radius(&query_point, 10.0);

Dependency Management

Dependency Hierarchy

Dependencies follow a strict hierarchy to avoid cycles:

Application Layer
    ↓
Domain Layer (Workspaces)
    ↓
Infrastructure Layer (Primitives)
    ↓
External Dependencies (tokio, serde, etc.)

Shared Dependencies

Common dependencies are defined at the root workspace:

[workspace.dependencies]
# Async runtime
tokio = { version = "1.35", features = ["full"] }

# Serialization
serde = { version = "1.0", features = ["derive"] }
serde_json = "1.0"

# Error handling
thiserror = "1.0"
anyhow = "1.0"

# Crypto
ring = "0.17"
ed25519-dalek = "2.0"

# Network
hyper = "1.0"
quinn = "0.10"

Feature Flags

Fine-grained control over functionalities:

[features]
default = ["std"]
std = ["avx-std"]
alloc = ["avx-alloc"]
async = ["tokio"]
gpu = ["cuda", "rocm"]
cuda = ["cudarc"]
rocm = ["hip"]
simd = []

Performance

Optimization Strategies

1. Zero-Copy Operations

// Use slices to avoid copies
pub fn process_data(data: &[u8]) -> &[u8] {
    &data[10..20]  // Zero-copy slice
}

// Reusable buffer
let mut buffer = Vec::with_capacity(1024);
loop {
    buffer.clear();
    read_data(&mut buffer)?;
    process(&buffer)?;
}

2. SIMD Vectorization

use std::simd::{f32x8, SimdFloat};

fn vector_add_simd(a: &[f32], b: &[f32], c: &mut [f32]) {
    for i in (0..a.len()).step_by(8) {
        let va = f32x8::from_slice(&a[i..]);
        let vb = f32x8::from_slice(&b[i..]);
        let vc = va + vb;
        vc.copy_to_slice(&mut c[i..]);
    }
}

3. Memory Pool

use avx_alloc::Pool;

let pool = Pool::new(1024);
let buf1 = pool.allocate(256);
let buf2 = pool.allocate(512);
// Buffers automatically reused

4. Async Batching

use tokio::time::{interval, Duration};

let mut batch = Vec::new();
let mut ticker = interval(Duration::from_millis(100));

loop {
    tokio::select! {
        item = receiver.recv() => {
            batch.push(item);
            if batch.len() >= 100 {
                process_batch(&batch).await;
                batch.clear();
            }
        }
        _ = ticker.tick() => {
            if !batch.is_empty() {
                process_batch(&batch).await;
                batch.clear();
            }
        }
    }
}

Benchmarks

All packages include benchmarks with Criterion:

use criterion::{black_box, criterion_group, criterion_main, Criterion};

fn benchmark_hash(c: &mut Criterion) {
    c.bench_function("sha256", |b| {
        let data = vec![0u8; 1024];
        b.iter(|| {
            avx_hash::sha256(black_box(&data))
        });
    });
}

criterion_group!(benches, benchmark_hash);
criterion_main!(benches);

Security

Security Practices

1. Memory Safety

• Minimal use of unsafe
• All unsafe is documented and audited
• Extensive testing with Miri

2. Constant-Time Operations

// Constant-time comparison to prevent timing attacks
use subtle::ConstantTimeEq;

pub fn verify_mac(expected: &[u8], actual: &[u8]) -> bool {
    expected.ct_eq(actual).into()
}

3. Secure Defaults

// Secure defaults
impl Default for CryptoConfig {
    fn default() -> Self {
        Self {
            algorithm: Algorithm::Aes256Gcm,  // Strong by default
            key_size: 256,
            iterations: 100_000,  // PBKDF2
        }
    }
}

4. Dependency Auditing

# deny.toml - Cargo deny configuration
[advisories]
db-path = "~/.cargo/advisory-db"
db-urls = ["https://github.com/rustsec/advisory-db"]
vulnerability = "deny"
unmaintained = "warn"
yanked = "deny"

Security Audits

Critical packages undergo regular audits:

• Third-party code auditing
• Continuous fuzzing
• Static analysis with Clippy and cargo-audit
• Penetration testing