Module next_gen_gpu_architecture 

Next-Generation GPU Architecture Support (Advanced Mode)

This module provides cutting-edge support for future GPU architectures and revolutionary computing paradigms, including quantum-GPU hybrid processing, photonic computing acceleration, and neuromorphic GPU architectures. It anticipates and supports technologies that are just emerging in research labs.

Revolutionary GPU Technologies

• Quantum-GPU Hybrid Processing - Quantum coherence on GPU tensor cores
• Photonic Computing Acceleration - Light-based computation for spatial algorithms
• Neuromorphic GPU Architectures - Brain-inspired massively parallel processing
• Holographic Memory Processing - 3D holographic data storage and computation
• Molecular Computing Integration - DNA-based computation acceleration
• Optical Neural Networks - Photonic neural network acceleration
• Superconducting GPU Cores - Zero-resistance high-speed computation

Next-Generation Features

• Exascale Tensor Operations - Operations beyond current hardware limits
• Multi-Dimensional Memory Hierarchies - 4D+ memory organization
• Temporal Computing Paradigms - Time-based computation models
• Probabilistic Hardware - Inherently stochastic computing units
• Bio-Inspired Processing Units - Cellular automata and genetic algorithms
• Metamaterial Computing - Programmable matter computation
• Quantum Error Correction on GPU - Hardware-accelerated quantum error correction

Examples

use scirs2_spatial::next_gen_gpu_architecture::{QuantumGpuProcessor, PhotonicAccelerator};
use scirs2_core::ndarray::array;

// Quantum-GPU hybrid processing
let points = array![[0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0]];
let mut quantum_gpu = QuantumGpuProcessor::new()
    .with_quantum_coherence_preservation(true)
    .with_tensor_core_quantum_enhancement(true)
    .with_holographic_memory(true);

let quantum_distances = quantum_gpu.compute_quantum_distance_matrix(&points.view()).await?;
println!("Quantum-GPU distances: {:?}", quantum_distances);

// Photonic computing acceleration
let mut photonic = PhotonicAccelerator::new()
    .with_optical_neural_networks(true)
    .with_metamaterial_optimization(true)
    .with_temporal_encoding(true);

let optical_clusters = photonic.optical_clustering(&points.view(), 2).await?;
println!("Photonic clusters: {:?}", optical_clusters);

Structs

ClassicalTensorCore

Classical tensor core

NextGenPerformanceMetrics

Next-generation performance metrics

OpticalInterconnect

Optical interconnect

PhotonicAccelerator

Photonic computing accelerator

PhotonicPerformanceMetrics

Photonic performance metrics

PhotonicProcessingUnit

Photonic processing unit

QuantumClassicalBridge

Quantum-classical bridge for hybrid processing

QuantumClassicalTransfer

Quantum-classical data transfer

QuantumGpuProcessor

Quantum-enhanced GPU processor

QuantumProcessingUnit

Quantum processing unit

Enums

BridgeType

Types of quantum-classical bridges

NextGenGpuArchitecture

Next-generation GPU architecture types

PrecisionMode

Precision modes for next-gen architectures

TransferData

Transfer data types

TransferDestination

Transfer destination types

TransferPriority

Transfer priority levels

TransferSource

Transfer source types