Module memory_optimization 

Advanced Memory Optimization for ToRSh Tensor Operations

This module provides cutting-edge memory management optimizations that minimize allocation overhead, reduce memory fragmentation, and maximize cache efficiency for tensor operations.

Features

• Zero-Copy Memory Management: Advanced memory reuse strategies
• Cache-Aware Allocation: Memory layout optimization for CPU cache hierarchy
• Anti-Fragmentation: Memory pooling and defragmentation algorithms
• NUMA-Aware Allocation: Non-uniform memory access optimization
• Predictive Allocation: ML-based memory usage prediction and pre-allocation
• Memory Compression: Transparent memory compression for large tensors

Structs

AdvancedMemoryPool

Memory pool for efficient tensor allocation

AggregateMemoryStats

Aggregate memory statistics across all type pools

CompressionStats

Compression statistics

DefragmentationReport

Defragmentation report

GlobalMemoryOptimizer

Global memory optimization manager

MemoryConfig

Advanced memory optimization configuration

MemoryStats

Memory allocation statistics