oxirs-vec 0.2.4

Vector index abstractions for semantic similarity and AI-augmented querying
Documentation
//! GPU acceleration engine implementation

use super::{GpuConfig, GpuDevice, GpuBuffer};
use crate::{Vector, VectorData, similarity::SimilarityMetric};
use anyhow::Result;
use std::collections::HashMap;
use std::sync::{Arc, Mutex};
use parking_lot::RwLock;

/// GPU acceleration engine for vector operations
pub struct GpuAccelerator {
    config: GpuConfig,
    device: GpuDevice,
    memory_pool: Arc<Mutex<Vec<GpuBuffer>>>,
    kernel_cache: Arc<RwLock<HashMap<String, CudaKernel>>>,
    performance_stats: Arc<RwLock<GpuPerformanceStats>>,
}

/// CUDA kernel representation
#[derive(Debug)]
pub struct CudaKernel {
    // Kernel implementation details would go here
    name: String,
    device_id: i32,
}

/// GPU performance statistics
#[derive(Debug, Default)]
pub struct GpuPerformanceStats {
    pub total_operations: u64,
    pub total_time_ms: f64,
    pub memory_transfers: u64,
    pub kernel_launches: u64,
}

impl GpuAccelerator {
    /// Create new GPU accelerator with specified configuration
    pub fn new(config: GpuConfig) -> Result<Self> {
        let device = super::get_gpu_device(config.device_id)?;

        Ok(Self {
            config,
            device,
            memory_pool: Arc::new(Mutex::new(Vec::new())),
            kernel_cache: Arc::new(RwLock::new(HashMap::new())),
            performance_stats: Arc::new(RwLock::new(GpuPerformanceStats::default())),
        })
    }

    /// Calculate similarity between vectors using GPU
    pub fn calculate_similarity(
        &self,
        query: &Vector,
        vectors: &[Vector],
        metric: SimilarityMetric,
    ) -> Result<Vec<f32>> {
        // GPU similarity calculation implementation would go here
        // For now, return a placeholder implementation
        Ok(vec![0.0; vectors.len()])
    }

    /// Batch process vectors on GPU
    pub fn batch_process(&self, vectors: &[Vector]) -> Result<Vec<Vector>> {
        // GPU batch processing implementation would go here
        Ok(vectors.to_vec())
    }

    /// Get GPU device information
    pub fn device(&self) -> &GpuDevice {
        &self.device
    }

    /// Get configuration
    pub fn config(&self) -> &GpuConfig {
        &self.config
    }
}