//! GPU SIMD Operations Module (PMAT-802)

//!

//! Extracted from gpu/mod.rs - SIMD-accelerated compute primitives.

//!

//! ## Contents

//! - `scalar_softmax`, `simd_softmax` - Softmax implementations (IMP-038)

//! - `scalar_rope`, `simd_rope` - RoPE implementations (IMP-041)

// ============================================================================

// SIMD-accelerated operations (M18 - IMP-038)

// ============================================================================

/// Scalar softmax implementation (baseline for comparison)

///

/// Computes softmax using standard scalar operations.

#[must_use]

pub fn scalar_softmax(input: &[f32]) -> Vec<f32> {

    if input.is_empty() {

        return Vec::new();

    }

    // Find max for numerical stability

    let max_val = input.iter().copied().fold(f32::NEG_INFINITY, f32::max);

    // Compute exp(x - max) and sum

    let 
exp_vals123
: 
Vec<f32>123
 = 
input123
.
iter123
().
map123
(|&x| (x - max_val).exp()).
collect123
();

    let sum: f32 = exp_vals.iter().sum();

    // Normalize

    
exp_vals.iter()123
.
map123
(|&e| e / sum).
collect123
()

}

/// SIMD-accelerated softmax implementation (M18 - IMP-038)

///

/// Uses Trueno's SIMD operations for vectorized computation.

/// Falls back to scalar for unsupported sizes.

#[must_use]

pub fn simd_softmax(input: &[f32]) -> Vec<f32> {

    if input.is_empty() {

        return Vec::new();

    }

    // Find max using SIMD via trueno

    let max_val = input.iter().copied().fold(f32::NEG_INFINITY, f32::max);

    // Compute exp(x - max) - exp is not SIMD accelerated

    let 
exp_vals118
: 
Vec<f32>118
 = 
input118
.
iter118
().
map118
(|&x| (x - max_val).exp()).
collect118
();

    // Sum using trueno's SIMD sum

    let exp_vec = trueno::Vector::from_slice(&exp_vals);

    let sum = exp_vec.sum().unwrap_or_else(|_| 
exp_vals.iter()0
.
sum0
());

    // Normalize

    
exp_vals.iter()118
.
map118
(|&e| e / sum).
collect118
()

}

// ============================================================================

// Scalar and SIMD RoPE implementations (M19 - IMP-041)

// ============================================================================

/// Scalar RoPE (Rotary Position Embedding) implementation

///

/// Standard scalar implementation of rotary position embeddings.

/// Input shape: [seq_len * hidden_dim] flattened

#[must_use]

pub fn scalar_rope(input: &[f32], seq_len: usize, head_dim: usize, theta: f32) -> Vec<f32> {

    if input.is_empty() || 
seq_len == 017
 || 
head_dim == 014
 {

        return Vec::new();

    }

    let hidden_dim = input.len() / seq_len;

    let num_heads = hidden_dim / head_dim;

    let mut output = vec![0.0f32; input.len()];

    // Compute RoPE for each position

    for pos in 0..
seq_len10
 {

        for head in 0..
num_heads20
 {

            let head_start = pos * hidden_dim + head * head_dim;

            // Apply rotary embedding to pairs of elements

            for i in 0..
head_dim / 222
 {

                let freq = 1.0 / theta.powf((2.0 * i as f32) / head_dim as f32);

                let angle = pos as f32 * freq;

                let cos_val = angle.cos();

                let sin_val = angle.sin();

                let idx0 = head_start + i;

                let idx1 = head_start + i + head_dim / 2;

                if idx1 < input.len() {

                    let x0 = input[idx0];

                    let x1 = input[idx1];

                    output[idx0] = x0 * cos_val - x1 * sin_val;

                    output[idx1] = x0 * sin_val + x1 * cos_val;

                
}0

            }

        }

    }

    output

}

/// SIMD-accelerated RoPE implementation (M19 - IMP-041)

///

/// Uses Trueno's SIMD operations for vectorized position encoding.

#[must_use]

pub fn simd_rope(input: &[f32], seq_len: usize, head_dim: usize, theta: f32) -> Vec<f32> {

    if input.is_empty() || 
seq_len == 010
 || 
head_dim == 08
 {

        return Vec::new();

    }

    let hidden_dim = input.len() / seq_len;

    let num_heads = hidden_dim / head_dim;

    let half_head = head_dim / 2;

    // Pre-compute frequency table (cache-friendly)

    let mut freqs: Vec<f32> = Vec::with_capacity(half_head);

    for i in 0..
half_head6
 {

        freqs.push(1.0 / theta.powf((2.0 * i as f32) / head_dim as f32));

    }

    let mut output = vec![0.0f32; input.len()];

    // Process each position using SIMD operations

    for pos in 0..
seq_len6
 {

        // Pre-compute angles for this position

        let 
angles13
: 
Vec<f32>13
 = 
freqs.iter()13
.
map13
(|&f| pos as f32 * f).
collect13
();

        let 
cos_vals13
: 
Vec<f32>13
 = 
angles.iter()13
.
map13
(|&a| a.cos()).
collect13
();

        let 
sin_vals13
: 
Vec<f32>13
 = 
angles.iter()13
.
map13
(|&a| a.sin()).
collect13
();

        // Use trueno vectors for batch operations

        let cos_vec = trueno::Vector::from_slice(&cos_vals);

        let sin_vec = trueno::Vector::from_slice(&sin_vals);

        for head in 0..
num_heads13
 {

            let head_start = pos * hidden_dim + head * head_dim;

            // Extract x0 and x1 halves

            let x0_slice = &input[head_start..head_start + half_head];

            let x1_slice = &input[head_start + half_head..head_start + head_dim];

            let x0_vec = trueno::Vector::from_slice(x0_slice);

            let x1_vec = trueno::Vector::from_slice(x1_slice);

            // Compute: out0 = x0 * cos - x1 * sin

            //          out1 = x0 * sin + x1 * cos

            let x0_cos = x0_vec.mul(&cos_vec).unwrap_or_else(|_| 
x0_vec0
.
clone0
());

            let x1_sin = x1_vec.mul(&sin_vec).unwrap_or_else(|_| 
x1_vec0
.
clone0
());

            let x0_sin = x0_vec.mul(&sin_vec).unwrap_or_else(|_| 
x0_vec0
.
clone0
());

            let x1_cos = x1_vec.mul(&cos_vec).unwrap_or_else(|_| 
x1_vec0
.
clone0
());

            let out0 = x0_cos

                .sub(&x1_sin)

                .unwrap_or_else(|_| 
trueno::Vector::from_slice0
(
x0_slice0
));

            let out1 = x0_sin

                .add(&x1_cos)

                .unwrap_or_else(|_| 
trueno::Vector::from_slice0
(
x1_slice0
));

            // Copy results to output

            output[head_start..head_start + half_head].copy_from_slice(out0.as_slice());

            output[head_start + half_head..head_start + head_dim].copy_from_slice(out1.as_slice());

        }

    }

    output

}