Module advanced_tensor_cores 

Advanced Tensor Cores and Automatic Kernel Tuning Framework

This module provides AI-driven optimization and adaptive management for tensor cores and automatic kernel tuning in Advanced mode, enabling intelligent performance optimization across diverse GPU architectures and workloads.

Features

• AI-Driven Optimization: Machine learning models for performance prediction and optimization
• Adaptive Kernel Tuning: Real-time adaptation based on workload characteristics
• Multi-Architecture Support: Unified interface for NVIDIA, AMD, Apple, and other GPU architectures
• Performance Analytics: Comprehensive monitoring and performance profiling
• Intelligent Caching: Smart caching of optimized configurations with predictive prefetching
• Real-time Learning: Continuous improvement from execution feedback
• Advanced Scheduling: Workload-aware resource allocation and scheduling
• Energy Optimization: Power-efficient computing with dynamic voltage and frequency scaling

Note: This module requires the gpu feature to be enabled.

Re-exports

pub use caching::*;

pub use hardware::*;

pub use monitoring::*;

pub use operations::*;

pub use optimization::*;

Modules

caching

Smart caching and prefetching systems for tensor operations

hardware

Hardware profiling and environment detection for tensor operations

monitoring

Real-time monitoring, analytics, and alerting for tensor operations

operations

Tensor operations, performance prediction, and adaptive scheduling

optimization

AI-driven optimization and learning algorithms for tensor operations

Structs

AdvancedTensorConfig

Configuration for advanced tensor core operations

AdvancedTensorCoreCoordinator

Central coordinator for advanced tensor cores and kernel tuning

EnergyEfficiencyMetrics

Energy efficiency metrics

EnergyOptimizationResult

Energy optimization result

LearningProgress

Learning progress tracking

OptimizationRecommendation

Optimization recommendation

PerformanceDataPoint

Performance data point for learning

PerformanceStatistics

Performance statistics summary

ResourceUtilization

Resource utilization tracking

TensorCoreAnalytics

Comprehensive tensor core analytics

ThroughputStatistics

Throughput statistics

Enums

ComplexityLevel

Complexity levels for recommendations

ModelType

Types of machine learning models

RecommendationType

Types of optimization recommendations

TrendDirection

Trend directions