amari 0.12.3

//! Phase 4B: GPU-Compatible Verification Contracts
//!
//! This module implements verification contracts specifically designed for GPU environments
//! where traditional phantom types face significant constraints. The design focuses on
//! boundary verification, performance-aware checking, and platform-adaptive strategies.

use std::marker::PhantomData;
use std::time::{Duration, Instant};
use amari_core::Multivector;

/// GPU-specific verification constraints and limitations
#[derive(Debug, Clone, Copy)]
pub struct GpuConstraints {
    /// Maximum memory overhead for verification data (in bytes)
    pub max_memory_overhead: u64,
    /// Maximum compute overhead per operation (in microseconds)
    pub max_compute_overhead_us: u64,
    /// SIMT execution compatibility requirement
    pub simt_compatible: bool,
    /// GPU memory hierarchy considerations
    pub memory_tier: GpuMemoryTier,
}

/// GPU memory hierarchy tiers with different verification strategies
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum GpuMemoryTier {
    /// Registers - no verification overhead allowed
    Register,
    /// Shared memory - minimal verification
    Shared,
    /// Global memory - bounded verification
    Global,
    /// Host memory - full verification available
    Host,
}

/// Verification error types specific to GPU environments
#[derive(Debug, Clone)]
pub enum GpuVerificationError {
    /// Memory tier constraint violation
    MemoryTierViolation { tier: GpuMemoryTier, operation: String },
    /// SIMT execution divergence detected
    SimtDivergence { warp_id: u32, thread_mask: u32 },
    /// GPU resource exhaustion
    ResourceExhaustion { resource: String, limit: u64 },
    /// Kernel execution failure
    KernelFailure { kernel: String, error: String },
    /// Mathematical invariant violation detected at GPU boundary
    BoundaryInvariantViolation { operation: String, details: String },
}

/// GPU-aware verification level that adapts to hardware constraints
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum GpuVerificationLevel {
    /// No verification - maximum performance
    None,
    /// Boundary-only verification at kernel launch/completion
    Boundary,
    /// Statistical verification using warp-level sampling
    WarpSampling { sample_rate: f32 },
    /// Thread-block level verification
    BlockLevel,
    /// Full verification (host-side only)
    HostSide,
}

/// GPU verification context that manages verification across device/host boundary
pub struct GpuVerificationContext<const P: usize, const Q: usize, const R: usize> {
    constraints: GpuConstraints,
    level: GpuVerificationLevel,
    device_verification_enabled: bool,
    host_verification_enabled: bool,
    operation_count: u64,
    total_overhead: Duration,
    _phantom: PhantomData<(P, Q, R)>,
}

impl<const P: usize, const Q: usize, const R: usize> GpuVerificationContext<P, Q, R> {
    /// Create GPU verification context with hardware detection
    pub fn new(constraints: GpuConstraints) -> Self {
        let level = Self::determine_optimal_gpu_level(constraints);

        Self {
            constraints,
            level,
            device_verification_enabled: Self::can_verify_on_device(constraints),
            host_verification_enabled: true,
            operation_count: 0,
            total_overhead: Duration::ZERO,
            _phantom: PhantomData,
        }
    }

    /// Determine optimal verification level based on GPU constraints
    fn determine_optimal_gpu_level(constraints: GpuConstraints) -> GpuVerificationLevel {
        match constraints.memory_tier {
            GpuMemoryTier::Register => GpuVerificationLevel::None,
            GpuMemoryTier::Shared => {
                if constraints.max_compute_overhead_us < 10 {
                    GpuVerificationLevel::None
                } else {
                    GpuVerificationLevel::Boundary
                }
            }
            GpuMemoryTier::Global => {
                if constraints.simt_compatible {
                    GpuVerificationLevel::WarpSampling { sample_rate: 0.1 }
                } else {
                    GpuVerificationLevel::BlockLevel
                }
            }
            GpuMemoryTier::Host => GpuVerificationLevel::HostSide,
        }
    }

    /// Check if verification can be performed on device
    fn can_verify_on_device(constraints: GpuConstraints) -> bool {
        constraints.max_memory_overhead > 1024 && // At least 1KB overhead allowed
        constraints.max_compute_overhead_us > 50   // At least 50 microseconds allowed
    }

    /// Verify GPU kernel launch with pre-conditions
    pub async fn verify_kernel_launch(
        &mut self,
        kernel_name: &str,
        input_data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        let start = Instant::now();
        self.operation_count += 1;

        match self.level {
            GpuVerificationLevel::None => Ok(()),
            GpuVerificationLevel::Boundary |
            GpuVerificationLevel::WarpSampling { .. } |
            GpuVerificationLevel::BlockLevel => {
                self.verify_kernel_preconditions(kernel_name, input_data).await
            }
            GpuVerificationLevel::HostSide => {
                self.verify_host_preconditions(kernel_name, input_data).await
            }
        }?;

        self.total_overhead += start.elapsed();
        Ok(())
    }

    /// Verify GPU kernel completion with post-conditions
    pub async fn verify_kernel_completion(
        &mut self,
        kernel_name: &str,
        output_data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        let start = Instant::now();

        match self.level {
            GpuVerificationLevel::None => Ok(()),
            GpuVerificationLevel::Boundary |
            GpuVerificationLevel::WarpSampling { .. } |
            GpuVerificationLevel::BlockLevel => {
                self.verify_kernel_postconditions(kernel_name, output_data).await
            }
            GpuVerificationLevel::HostSide => {
                self.verify_host_postconditions(kernel_name, output_data).await
            }
        }?;

        self.total_overhead += start.elapsed();
        Ok(())
    }

    /// Verify memory transfer from host to device
    pub async fn verify_host_to_device_transfer(
        &mut self,
        data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        // Verify data integrity before GPU transfer
        for (i, mv) in data.iter().enumerate() {
            if !mv.magnitude().is_finite() {
                return Err(GpuVerificationError::BoundaryInvariantViolation {
                    operation: "host_to_device_transfer".to_string(),
                    details: format!("Non-finite magnitude at index {}", i),
                });
            }

            // Check for NaN or infinity in coefficients
            for j in 0..8 {
                let coeff = mv.get(j);
                if !coeff.is_finite() {
                    return Err(GpuVerificationError::BoundaryInvariantViolation {
                        operation: "host_to_device_transfer".to_string(),
                        details: format!("Non-finite coefficient at index {} basis {}", i, j),
                    });
                }
            }
        }

        // Check memory constraints
        let transfer_size = data.len() * std::mem::size_of::<Multivector<P, Q, R>>();
        if transfer_size as u64 > self.constraints.max_memory_overhead {
            return Err(GpuVerificationError::ResourceExhaustion {
                resource: "transfer_memory".to_string(),
                limit: self.constraints.max_memory_overhead,
            });
        }

        Ok(())
    }

    /// Verify memory transfer from device to host
    pub async fn verify_device_to_host_transfer(
        &mut self,
        data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        // Verify computational integrity after GPU processing
        for (i, mv) in data.iter().enumerate() {
            // Verify magnitude is reasonable (not too large from numerical errors)
            let magnitude = mv.magnitude();
            if magnitude > 1e10 {
                return Err(GpuVerificationError::BoundaryInvariantViolation {
                    operation: "device_to_host_transfer".to_string(),
                    details: format!("Magnitude too large at index {}: {}", i, magnitude),
                });
            }

            // Verify no GPU computation artifacts
            if !magnitude.is_finite() {
                return Err(GpuVerificationError::BoundaryInvariantViolation {
                    operation: "device_to_host_transfer".to_string(),
                    details: format!("GPU computation produced non-finite result at index {}", i),
                });
            }
        }

        Ok(())
    }

    /// Verify batch geometric product operation on GPU
    pub async fn verify_batch_geometric_product(
        &mut self,
        a_batch: &[Multivector<P, Q, R>],
        b_batch: &[Multivector<P, Q, R>],
        result_batch: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        if a_batch.len() != b_batch.len() || b_batch.len() != result_batch.len() {
            return Err(GpuVerificationError::BoundaryInvariantViolation {
                operation: "batch_geometric_product".to_string(),
                details: "Batch size mismatch".to_string(),
            });
        }

        match self.level {
            GpuVerificationLevel::None => Ok(()),
            GpuVerificationLevel::Boundary => {
                // Verify only first and last elements
                self.verify_single_geometric_product(&a_batch[0], &b_batch[0], &result_batch[0]).await?;
                if a_batch.len() > 1 {
                    let last = a_batch.len() - 1;
                    self.verify_single_geometric_product(&a_batch[last], &b_batch[last], &result_batch[last]).await?;
                }
                Ok(())
            }
            GpuVerificationLevel::WarpSampling { sample_rate } => {
                // Verify sampled elements based on sample rate
                let sample_count = ((a_batch.len() as f32) * sample_rate).ceil() as usize;
                let step = a_batch.len() / sample_count.max(1);

                for i in (0..a_batch.len()).step_by(step) {
                    self.verify_single_geometric_product(&a_batch[i], &b_batch[i], &result_batch[i]).await?;
                }
                Ok(())
            }
            GpuVerificationLevel::BlockLevel => {
                // Verify block-aligned elements (64 elements per block)
                for i in (0..a_batch.len()).step_by(64) {
                    self.verify_single_geometric_product(&a_batch[i], &b_batch[i], &result_batch[i]).await?;
                }
                Ok(())
            }
            GpuVerificationLevel::HostSide => {
                // Verify all elements on host
                for i in 0..a_batch.len() {
                    self.verify_single_geometric_product(&a_batch[i], &b_batch[i], &result_batch[i]).await?;
                }
                Ok(())
            }
        }
    }

    /// Verify single geometric product with mathematical properties
    async fn verify_single_geometric_product(
        &self,
        a: &Multivector<P, Q, R>,
        b: &Multivector<P, Q, R>,
        result: &Multivector<P, Q, R>,
    ) -> Result<(), GpuVerificationError> {
        // Compute expected result on host for verification
        let expected = a.geometric_product(b);

        // Check numerical equivalence within GPU precision tolerance
        let tolerance = 1e-6; // GPU single precision tolerance
        for i in 0..8 {
            let diff = (result.get(i) - expected.get(i)).abs();
            if diff > tolerance {
                return Err(GpuVerificationError::BoundaryInvariantViolation {
                    operation: "geometric_product_verification".to_string(),
                    details: format!("Coefficient {} differs by {} (tolerance: {})", i, diff, tolerance),
                });
            }
        }

        Ok(())
    }

    /// Kernel precondition verification
    async fn verify_kernel_preconditions(
        &self,
        kernel_name: &str,
        input_data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        // Check data size constraints for GPU kernels
        if input_data.len() > 1_000_000 {
            return Err(GpuVerificationError::ResourceExhaustion {
                resource: "input_batch_size".to_string(),
                limit: 1_000_000,
            });
        }

        // Verify SIMT compatibility if required
        if self.constraints.simt_compatible && input_data.len() % 32 != 0 {
            return Err(GpuVerificationError::SimtDivergence {
                warp_id: 0,
                thread_mask: 0xFFFFFFFF,
            });
        }

        // Check for values that might cause GPU numerical issues
        for (i, mv) in input_data.iter().enumerate() {
            let magnitude = mv.magnitude();
            if magnitude > 1e20 || magnitude < 1e-20 {
                return Err(GpuVerificationError::BoundaryInvariantViolation {
                    operation: kernel_name.to_string(),
                    details: format!("Input magnitude {} at index {} may cause GPU precision issues", magnitude, i),
                });
            }
        }

        Ok(())
    }

    /// Kernel postcondition verification
    async fn verify_kernel_postconditions(
        &self,
        kernel_name: &str,
        output_data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        // Verify output data integrity
        for (i, mv) in output_data.iter().enumerate() {
            if !mv.magnitude().is_finite() {
                return Err(GpuVerificationError::KernelFailure {
                    kernel: kernel_name.to_string(),
                    error: format!("Non-finite output at index {}", i),
                });
            }

            // Check for GPU computation artifacts
            for j in 0..8 {
                let coeff = mv.get(j);
                if coeff.is_nan() {
                    return Err(GpuVerificationError::KernelFailure {
                        kernel: kernel_name.to_string(),
                        error: format!("NaN coefficient at index {} basis {}", i, j),
                    });
                }
            }
        }

        Ok(())
    }

    /// Host-side precondition verification (full phantom type support)
    async fn verify_host_preconditions(
        &self,
        _kernel_name: &str,
        input_data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        // Full mathematical property verification on host
        for mv in input_data {
            if !Self::verify_clifford_properties(mv) {
                return Err(GpuVerificationError::BoundaryInvariantViolation {
                    operation: "host_precondition_check".to_string(),
                    details: "Clifford algebra properties violated".to_string(),
                });
            }
        }
        Ok(())
    }

    /// Host-side postcondition verification
    async fn verify_host_postconditions(
        &self,
        _kernel_name: &str,
        output_data: &[Multivector<P, Q, R>],
    ) -> Result<(), GpuVerificationError> {
        // Full mathematical property verification on host
        for mv in output_data {
            if !Self::verify_clifford_properties(mv) {
                return Err(GpuVerificationError::BoundaryInvariantViolation {
                    operation: "host_postcondition_check".to_string(),
                    details: "Output violates Clifford algebra properties".to_string(),
                });
            }
        }
        Ok(())
    }

    /// Verify Clifford algebra mathematical properties
    fn verify_clifford_properties(mv: &Multivector<P, Q, R>) -> bool {
        // Check magnitude is non-negative and finite
        let magnitude = mv.magnitude();
        if !magnitude.is_finite() || magnitude < 0.0 {
            return false;
        }

        // Check all coefficients are finite
        for i in 0..8 {
            if !mv.get(i).is_finite() {
                return false;
            }
        }

        // Check signature constraints for specific algebras
        match (P, Q, R) {
            (3, 0, 0) => {
                // Euclidean 3D - additional checks could be added
                true
            }
            (1, 3, 0) => {
                // Minkowski spacetime - check signature constraints
                true
            }
            _ => true,
        }
    }

    /// Get GPU verification statistics
    pub fn get_gpu_stats(&self) -> GpuVerificationStats {
        GpuVerificationStats {
            level: self.level,
            operation_count: self.operation_count,
            total_overhead: self.total_overhead,
            device_verification_enabled: self.device_verification_enabled,
            host_verification_enabled: self.host_verification_enabled,
            constraints: self.constraints,
        }
    }

    /// Adapt verification level based on runtime performance
    pub fn adapt_verification_level(&mut self, target_overhead_ratio: f64) {
        let current_overhead_ms = self.total_overhead.as_millis() as f64;
        let operation_time_estimate = current_overhead_ms / self.operation_count as f64;

        if operation_time_estimate > target_overhead_ratio * 1000.0 {
            // Reduce verification level if overhead too high
            self.level = match self.level {
                GpuVerificationLevel::HostSide => GpuVerificationLevel::BlockLevel,
                GpuVerificationLevel::BlockLevel => GpuVerificationLevel::WarpSampling { sample_rate: 0.1 },
                GpuVerificationLevel::WarpSampling { sample_rate } if sample_rate > 0.01 => {
                    GpuVerificationLevel::WarpSampling { sample_rate: sample_rate * 0.5 }
                }
                _ => GpuVerificationLevel::Boundary,
            };
        }
    }
}

/// GPU verification statistics for performance monitoring
#[derive(Debug)]
pub struct GpuVerificationStats {
    pub level: GpuVerificationLevel,
    pub operation_count: u64,
    pub total_overhead: Duration,
    pub device_verification_enabled: bool,
    pub host_verification_enabled: bool,
    pub constraints: GpuConstraints,
}

/// GPU-verified multivector wrapper with boundary checking
pub struct GpuVerifiedMultivector<const P: usize, const Q: usize, const R: usize> {
    inner: Multivector<P, Q, R>,
    gpu_verified: bool,
    host_verified: bool,
    verification_level: GpuVerificationLevel,
    _phantom: PhantomData<(P, Q, R)>,
}

impl<const P: usize, const Q: usize, const R: usize> GpuVerifiedMultivector<P, Q, R> {
    /// Create GPU-verified multivector with boundary validation
    pub fn new_gpu_verified(
        multivector: Multivector<P, Q, R>,
        context: &GpuVerificationContext<P, Q, R>,
    ) -> Result<Self, GpuVerificationError> {
        // Always verify on host side
        if !GpuVerificationContext::<P, Q, R>::verify_clifford_properties(&multivector) {
            return Err(GpuVerificationError::BoundaryInvariantViolation {
                operation: "gpu_verified_creation".to_string(),
                details: "Input violates Clifford algebra properties".to_string(),
            });
        }

        Ok(Self {
            inner: multivector,
            gpu_verified: context.device_verification_enabled,
            host_verified: true,
            verification_level: context.level,
            _phantom: PhantomData,
        })
    }

    /// Perform verified batch geometric product on GPU
    pub async fn batch_geometric_product_gpu_verified(
        a_batch: &[Self],
        b_batch: &[Self],
        context: &mut GpuVerificationContext<P, Q, R>,
    ) -> Result<Vec<Self>, GpuVerificationError> {
        // Extract inner multivectors
        let a_mvs: Vec<Multivector<P, Q, R>> = a_batch.iter().map(|v| v.inner).collect();
        let b_mvs: Vec<Multivector<P, Q, R>> = b_batch.iter().map(|v| v.inner).collect();

        // Verify kernel launch
        context.verify_kernel_launch("batch_geometric_product", &a_mvs).await?;

        // Simulate GPU computation (in real implementation, this would call GPU kernel)
        let mut result_mvs = Vec::with_capacity(a_mvs.len());
        for (a, b) in a_mvs.iter().zip(b_mvs.iter()) {
            result_mvs.push(a.geometric_product(b));
        }

        // Verify kernel completion
        context.verify_kernel_completion("batch_geometric_product", &result_mvs).await?;

        // Verify batch operation
        context.verify_batch_geometric_product(&a_mvs, &b_mvs, &result_mvs).await?;

        // Wrap results in verified containers
        let verified_results: Result<Vec<Self>, _> = result_mvs
            .into_iter()
            .map(|mv| Self::new_gpu_verified(mv, context))
            .collect();

        verified_results
    }

    /// Get underlying multivector (verified)
    pub fn inner(&self) -> &Multivector<P, Q, R> {
        &self.inner
    }

    /// Check if GPU verification was performed
    pub fn is_gpu_verified(&self) -> bool {
        self.gpu_verified
    }

    /// Check if host verification was performed
    pub fn is_host_verified(&self) -> bool {
        self.host_verified
    }

    /// Get verification level used
    pub fn verification_level(&self) -> GpuVerificationLevel {
        self.verification_level
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[tokio::test]
    async fn test_gpu_verification_context_creation() {
        let constraints = GpuConstraints {
            max_memory_overhead: 1024 * 1024, // 1MB
            max_compute_overhead_us: 1000,     // 1ms
            simt_compatible: true,
            memory_tier: GpuMemoryTier::Global,
        };

        let context = GpuVerificationContext::<3, 0, 0>::new(constraints);
        assert_eq!(context.level, GpuVerificationLevel::WarpSampling { sample_rate: 0.1 });
        assert!(context.device_verification_enabled);
    }

    #[tokio::test]
    async fn test_boundary_verification() {
        let constraints = GpuConstraints {
            max_memory_overhead: 512, // Low memory
            max_compute_overhead_us: 10, // Low overhead
            simt_compatible: false,
            memory_tier: GpuMemoryTier::Shared,
        };

        let mut context = GpuVerificationContext::<3, 0, 0>::new(constraints);

        let test_data = vec![
            Multivector::<3, 0, 0>::basis_vector(0),
            Multivector::<3, 0, 0>::basis_vector(1),
        ];

        let result = context.verify_kernel_launch("test_kernel", &test_data).await;
        assert!(result.is_ok());
    }

    #[tokio::test]
    async fn test_gpu_verified_multivector() {
        let constraints = GpuConstraints {
            max_memory_overhead: 1024 * 1024,
            max_compute_overhead_us: 1000,
            simt_compatible: true,
            memory_tier: GpuMemoryTier::Global,
        };

        let context = GpuVerificationContext::<3, 0, 0>::new(constraints);
        let mv = Multivector::<3, 0, 0>::basis_vector(0);

        let verified_mv = GpuVerifiedMultivector::new_gpu_verified(mv, &context);
        assert!(verified_mv.is_ok());

        let verified = verified_mv.unwrap();
        assert!(verified.is_host_verified());
        assert_eq!(verified.verification_level(), GpuVerificationLevel::WarpSampling { sample_rate: 0.1 });
    }

    #[tokio::test]
    async fn test_invalid_gpu_data_rejection() {
        let constraints = GpuConstraints {
            max_memory_overhead: 1024,
            max_compute_overhead_us: 100,
            simt_compatible: true,
            memory_tier: GpuMemoryTier::Global,
        };

        let context = GpuVerificationContext::<3, 0, 0>::new(constraints);

        // Create invalid multivector with NaN
        let mut invalid_mv = Multivector::<3, 0, 0>::zero();
        invalid_mv.set_scalar(f64::NAN);

        let result = GpuVerifiedMultivector::new_gpu_verified(invalid_mv, &context);
        assert!(result.is_err());

        if let Err(GpuVerificationError::BoundaryInvariantViolation { operation, .. }) = result {
            assert_eq!(operation, "gpu_verified_creation");
        } else {
            panic!("Expected BoundaryInvariantViolation error");
        }
    }

    #[test]
    fn test_verification_level_adaptation() {
        let constraints = GpuConstraints {
            max_memory_overhead: 1024 * 1024,
            max_compute_overhead_us: 1000,
            simt_compatible: true,
            memory_tier: GpuMemoryTier::Host,
        };

        let mut context = GpuVerificationContext::<3, 0, 0>::new(constraints);
        assert_eq!(context.level, GpuVerificationLevel::HostSide);

        // Simulate high overhead
        context.operation_count = 1;
        context.total_overhead = Duration::from_millis(2000);

        context.adapt_verification_level(0.1); // 10% overhead target

        // Should have reduced verification level
        assert_ne!(context.level, GpuVerificationLevel::HostSide);
    }
}