Struct GpuOptimizationContext 

pub struct GpuOptimizationContext { /* private fields */ }

GPU-accelerated optimization context

Implementations

impl GpuOptimizationContext

pub fn new(config: GpuOptimizationConfig) -> ScirsResult<Self>

Create a new GPU optimization context

pub fn config(&self) -> &GpuOptimizationConfig

Get the configuration

pub fn context(&self) -> &Arc<GpuContext>

Get the GPU context

pub fn allocate_workspace(&mut self, size: usize) -> ScirsResult<GpuWorkspace>

Allocate GPU memory for optimization data

pub fn transfer_to_gpu<T>( &self, data: &Array2<T>, ) -> ScirsResult<OptimGpuArray<T>>

where T: Clone + Send + Sync + 'static + GpuDataType,

Transfer data from CPU to GPU using scirs2-core GPU abstractions

pub fn transfer_from_gpu<T>( &self, gpu_data: &OptimGpuArray<T>, ) -> ScirsResult<Array2<T>>

where T: Clone + Send + Sync + Default + 'static + GpuDataType,

Transfer data from GPU to CPU using scirs2-core GPU abstractions

pub fn upload_array<T>(&self, data: &Array2<T>) -> ScirsResult<OptimGpuArray<T>>

where T: Clone + Send + Sync + 'static + GpuDataType,

Upload array to GPU (alias for transfer_to_gpu)

pub fn download_array<T>( &self, gpu_data: &OptimGpuArray<T>, ) -> ScirsResult<Array2<T>>

where T: Clone + Send + Sync + Default + 'static + GpuDataType,

Download array from GPU (alias for transfer_from_gpu)

pub fn evaluate_function_batch<F>( &self, function: &F, points: &Array2<f64>, ) -> ScirsResult<Array1<f64>>

where F: GpuFunction,

Execute batch function evaluation

pub fn evaluate_gradient_batch<F>( &self, function: &F, points: &Array2<f64>, ) -> ScirsResult<Array2<f64>>

where F: GpuFunction,

Execute batch gradient evaluation

pub fn compute_gradient_finite_diff<F>( &self, function: &F, x: &Array1<f64>, h: f64, ) -> ScirsResult<Array1<f64>>

where F: Fn(&ArrayView1<'_, f64>) -> f64,

Compute gradient using finite differences

pub fn compute_search_direction( &self, gradient: &Array1<f64>, ) -> ScirsResult<Array1<f64>>

Compute search direction (simple steepest descent for now)