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Memory Hierarchy and Data Locality for AI Systems

7 chapters · 32 lessons

1. 1. Memory Hierarchy Fundamentals

   4 lessons

   Understand the speed, capacity, and cost tradeoffs that define modern memory systems.

2. 2. Data Locality and Access Patterns

   5 lessons

   Learn how data placement relative to compute determines real-world performance.

3. 3. Tiered Memory Architecture

   5 lessons

   Design multi-tier memory systems that place data at the right distance from compute.

4. 4. Caching Strategies and Prefetching

   4 lessons

   Reduce data movement overhead through intelligent caching and predictive loading.

5. 5. Memory Optimization for AI Inference

   5 lessons

   Apply memory hierarchy principles to model serving and inference workloads.

6. 6. Retrieval and Embedding Systems

   4 lessons

   Design memory-efficient architectures for vector databases and retrieval pipelines.

7. 7. Diagnosing and Resolving Memory Bottlenecks

   5 lessons

   Use profiling tools and metrics to identify and fix memory performance issues.