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Memory Systems for Performance Engineering

7 chapters · 30 lessons

1. 1. Memory Hierarchy Fundamentals

   4 lessons

   Understand how registers, cache, DRAM, and storage form a performance hierarchy with distinct cost and speed tradeoffs.

2. 2. Profiling Memory Bottlenecks

   4 lessons

   Use profiling tools and metrics to distinguish compute-bound from memory-bound workloads and pinpoint access patterns.

3. 3. Optimizing Data Structures for Memory Efficiency

   5 lessons

   Design and refactor data structures to minimize cache misses, reduce memory footprint, and improve access locality.

4. 4. Memory Constraints in Database and Analytics Systems

   4 lessons

   Evaluate how DRAM capacity and bandwidth shape query performance, indexing strategies, and workload scaling.

5. 5. Memory Management in AI and ML Systems

   5 lessons

   Optimize memory usage for model inference, embedding indexes, and batch processing pipelines.

6. 6. Mobile and Edge Memory Optimization

   4 lessons

   Design memory-efficient applications for constrained devices with limited DRAM and battery budgets.

7. 7. Capacity Planning and Cost Optimization

   4 lessons

   Estimate memory requirements, evaluate hardware options, and optimize cloud and on-premises infrastructure costs.