scirs2-fft 0.4.2

#![allow(clippy::needless_range_loop)]
// The GPU kernel modules are not fully implemented yet
// This example demonstrates the planned features and interface

use std::f64::consts::PI;

#[allow(dead_code)]
fn main() {
    println!("GPU Kernel Optimization Example");
    println!("===============================\n");
    println!("This example is currently disabled as the GPU kernel optimization features are under development.");
    println!("The features demonstrated in this example will include:");

    println!("\n1. GPU Architecture Detection:");
    println!("   - NVIDIA GeForce RTX 3080: Compute 8.6, 10 GB memory");
    println!("   - NVIDIA GeForce GTX 1080: Compute 6.1, 8 GB memory");
    println!("   - AMD Radeon RX 6800 XT: Compute 9.0, 16 GB memory");

    println!("\n2. Kernel Configuration Options:");
    println!("   - Block size optimization (128, 256, 512, 1024 threads)");
    println!("   - Grid size auto-tuning");
    println!("   - Shared memory allocation");
    println!("   - Mixed precision computation");
    println!("   - Register per thread optimization");

    println!("\n3. Algorithm-Specific Optimizations:");
    println!("   - Sublinear FFT: Optimized for throughput");
    println!("   - Compressed Sensing: High accuracy mode");
    println!("   - Iterative: Low latency mode");
    println!("   - Frequency Pruning: Memory efficient mode");

    println!("\n4. Performance Metrics:");
    println!("   - Execution time (ms)");
    println!("   - Memory bandwidth (GB/s)");
    println!("   - Compute throughput (GFLOPS)");
    println!("   - GPU occupancy percentage");

    println!("\n5. Advanced Features:");
    println!("   - Tensor core acceleration");
    println!("   - Multi-GPU support");
    println!("   - Asynchronous execution");
    println!("   - Memory pooling");

    // Provide example of what the optimized kernel API will look like
    println!("\nPlanned API Usage:");
    println!("```rust");
    println!("// Create kernel launcher");
    println!("let launcher = KernelLauncher::new(factory);");
    println!();
    println!("// Configure kernel parameters");
    println!("let config = KernelConfig {{");
    println!("    blocksize: 256,");
    println!("    use_mixedprecision: true,");
    println!("    ..Default::default()");
    println!("}};");
    println!();
    println!("// Launch optimized sparse FFT kernel");
    println!("let stats = launcher.launch_sparse_fft_kernel(");
    println!("    inputsize, sparsity, algorithm, window");
    println!(");");
    println!("```");
}

// Helper function to demonstrate sparse signal creation
#[allow(dead_code)]
fn create_sparse_signal(n: usize, frequencies: &[(usize, f64)]) -> Vec<f64> {
    let mut signal = vec![0.0; n];
    for i in 0..n {
        let t = 2.0 * PI * (i as f64) / (n as f64);
        for &(freq, amp) in frequencies {
            signal[i] += amp * (freq as f64 * t).sin();
        }
    }
    signal
}