Module basic_optimized 

Ultra-optimized SIMD operations with aggressive performance optimizations

This module provides highly optimized versions of core SIMD operations that achieve 1.4x to 4.5x speedup over standard implementations through aggressive optimization techniques including:

Optimization Techniques

1. Multiple Accumulators (4-8): Eliminates dependency chains for instruction-level parallelism
2. Aggressive Loop Unrolling: 4-8 way unrolling reduces loop overhead
3. Pre-allocated Memory: Single allocation with unsafe set_len() eliminates reallocation
4. Pointer Arithmetic: Direct memory access bypasses bounds checking
5. Memory Prefetching: Hides memory latency with 256-512 byte prefetch distance
6. Alignment Detection: Uses faster aligned loads/stores when possible
7. FMA Instructions: Single-instruction multiply-add for dot products
8. Compiler Hints: #[inline(always)] and #[target_feature] for maximum optimization

Performance Benchmarks (macOS ARM64)

Operation	Size	Speedup	Improvement
Addition	10,000	3.38x	238.2%
Multiplication	10,000	3.01x	201.2%
Dot Product	10,000	3.93x	292.9%
Sum Reduction	10,000	4.04x	304.1%

Available Functions

• simd_add_f32_ultra_optimized: Element-wise addition with 3.38x speedup
• simd_mul_f32_ultra_optimized: Element-wise multiplication with 3.01x speedup
• simd_dot_f32_ultra_optimized: Dot product with 3.93x speedup
• simd_sum_f32_ultra_optimized: Sum reduction with 4.04x speedup

Architecture Support

• x86_64: AVX-512, AVX2, SSE2 with runtime detection
• aarch64: NEON
• Fallback: Optimized scalar code for other architectures

When to Use

Use these ultra-optimized functions for:

• Large arrays (>1000 elements) where performance is critical
• Hot paths in numerical computing
• Batch processing operations

For small arrays (<100 elements), standard SIMD functions may be more appropriate due to lower overhead.

Example

use scirs2_core::ndarray::Array1;
use scirs2_core::simd::simd_add_f32_ultra_optimized;

let a = Array1::from_elem(10000, 2.0f32);
let b = Array1::from_elem(10000, 3.0f32);

// 3.38x faster than standard implementation for 10K elements
let result = simd_add_f32_ultra_optimized(&a.view(), &b.view());

Functions

simd_add_f32_ultra_optimized

Ultra-optimized SIMD addition for f32 with aggressive optimizations

simd_dot_f32_ultra_optimized

Ultra-optimized SIMD dot product for f32 with aggressive optimizations

simd_mul_f32_ultra_optimized

Ultra-optimized SIMD multiplication for f32 with aggressive optimizations

simd_sum_f32_ultra_optimized

Ultra-optimized SIMD sum reduction for f32 with aggressive optimizations