use std::marker::PhantomData;
use std::time::{Duration, Instant};
use amari_core::Multivector;
#[derive(Debug, Clone, Copy)]
pub struct GpuConstraints {
pub max_memory_overhead: u64,
pub max_compute_overhead_us: u64,
pub simt_compatible: bool,
pub memory_tier: GpuMemoryTier,
}
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum GpuMemoryTier {
Register,
Shared,
Global,
Host,
}
#[derive(Debug, Clone)]
pub enum GpuVerificationError {
MemoryTierViolation { tier: GpuMemoryTier, operation: String },
SimtDivergence { warp_id: u32, thread_mask: u32 },
ResourceExhaustion { resource: String, limit: u64 },
KernelFailure { kernel: String, error: String },
BoundaryInvariantViolation { operation: String, details: String },
}
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum GpuVerificationLevel {
None,
Boundary,
WarpSampling { sample_rate: f32 },
BlockLevel,
HostSide,
}
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> {
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,
}
}
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,
}
}
fn can_verify_on_device(constraints: GpuConstraints) -> bool {
constraints.max_memory_overhead > 1024 && constraints.max_compute_overhead_us > 50 }
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(())
}
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(())
}
pub async fn verify_host_to_device_transfer(
&mut self,
data: &[Multivector<P, Q, R>],
) -> Result<(), GpuVerificationError> {
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),
});
}
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),
});
}
}
}
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(())
}
pub async fn verify_device_to_host_transfer(
&mut self,
data: &[Multivector<P, Q, R>],
) -> Result<(), GpuVerificationError> {
for (i, mv) in data.iter().enumerate() {
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),
});
}
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(())
}
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 => {
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 } => {
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 => {
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 => {
for i in 0..a_batch.len() {
self.verify_single_geometric_product(&a_batch[i], &b_batch[i], &result_batch[i]).await?;
}
Ok(())
}
}
}
async fn verify_single_geometric_product(
&self,
a: &Multivector<P, Q, R>,
b: &Multivector<P, Q, R>,
result: &Multivector<P, Q, R>,
) -> Result<(), GpuVerificationError> {
let expected = a.geometric_product(b);
let tolerance = 1e-6; 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(())
}
async fn verify_kernel_preconditions(
&self,
kernel_name: &str,
input_data: &[Multivector<P, Q, R>],
) -> Result<(), GpuVerificationError> {
if input_data.len() > 1_000_000 {
return Err(GpuVerificationError::ResourceExhaustion {
resource: "input_batch_size".to_string(),
limit: 1_000_000,
});
}
if self.constraints.simt_compatible && input_data.len() % 32 != 0 {
return Err(GpuVerificationError::SimtDivergence {
warp_id: 0,
thread_mask: 0xFFFFFFFF,
});
}
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(())
}
async fn verify_kernel_postconditions(
&self,
kernel_name: &str,
output_data: &[Multivector<P, Q, R>],
) -> Result<(), GpuVerificationError> {
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),
});
}
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(())
}
async fn verify_host_preconditions(
&self,
_kernel_name: &str,
input_data: &[Multivector<P, Q, R>],
) -> Result<(), GpuVerificationError> {
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(())
}
async fn verify_host_postconditions(
&self,
_kernel_name: &str,
output_data: &[Multivector<P, Q, R>],
) -> Result<(), GpuVerificationError> {
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(())
}
fn verify_clifford_properties(mv: &Multivector<P, Q, R>) -> bool {
let magnitude = mv.magnitude();
if !magnitude.is_finite() || magnitude < 0.0 {
return false;
}
for i in 0..8 {
if !mv.get(i).is_finite() {
return false;
}
}
match (P, Q, R) {
(3, 0, 0) => {
true
}
(1, 3, 0) => {
true
}
_ => true,
}
}
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,
}
}
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 {
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,
};
}
}
}
#[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,
}
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> {
pub fn new_gpu_verified(
multivector: Multivector<P, Q, R>,
context: &GpuVerificationContext<P, Q, R>,
) -> Result<Self, GpuVerificationError> {
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,
})
}
pub async fn batch_geometric_product_gpu_verified(
a_batch: &[Self],
b_batch: &[Self],
context: &mut GpuVerificationContext<P, Q, R>,
) -> Result<Vec<Self>, GpuVerificationError> {
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();
context.verify_kernel_launch("batch_geometric_product", &a_mvs).await?;
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));
}
context.verify_kernel_completion("batch_geometric_product", &result_mvs).await?;
context.verify_batch_geometric_product(&a_mvs, &b_mvs, &result_mvs).await?;
let verified_results: Result<Vec<Self>, _> = result_mvs
.into_iter()
.map(|mv| Self::new_gpu_verified(mv, context))
.collect();
verified_results
}
pub fn inner(&self) -> &Multivector<P, Q, R> {
&self.inner
}
pub fn is_gpu_verified(&self) -> bool {
self.gpu_verified
}
pub fn is_host_verified(&self) -> bool {
self.host_verified
}
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, max_compute_overhead_us: 1000, 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, max_compute_overhead_us: 10, 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);
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);
context.operation_count = 1;
context.total_overhead = Duration::from_millis(2000);
context.adapt_verification_level(0.1);
assert_ne!(context.level, GpuVerificationLevel::HostSide);
}
}