performance

A deep dive into how large language models actually run in production — why prefill is fast and decode is slow, how the KV cache works, sampling strategies like temperature and top-p, speculative decoding, and continuous batching with vLLM.

Understand where caches live, how cache-aside, read-through, write-through, and write-back differ, how to choose eviction policies, and how to prevent cache stampedes — with hit ratio math and a concrete cache-aside code snippet.

The five memory spaces a CUDA kernel can see and why they have wildly different speeds. Global vs shared vs constant vs local vs registers, coalesced access, bank conflicts, and a cheat-sheet table you'll actually reference.

Why GPUs eat CPUs for breakfast on some workloads and choke on others. Serial vs parallel execution, Amdahl's law, the latency-vs-throughput trade-off baked into silicon, and a rule of thumb for when to reach for a GPU.

Why your assets should never come from your origin. How a CDN's edge cache, geographic routing, and invalidation actually work, plus the cases where a CDN doesn't help (or quietly hurts).

The named caching patterns (cache-aside, read-through, write-through, write-behind), when each makes sense, and the failure modes that bite even experienced teams (thundering herd, stale invalidation, the second-hardest problem).

How to cut LLM bills 50-90% without sacrificing freshness. Covers the three caching layers (response, prefix, semantic), what each costs to build, and the cases where caching subtly breaks correctness.

Dive deep into the world of PostgreSQL indexes. Understand the core mechanics of B-tree, Hash, GIN, and GiST indexes, their optimal use cases, and how to choose the right indexing strategy to dramatically accelerate your database queries.

Explore Redis, a powerful open-source in-memory data store. Learn its core concepts, why it's used, its versatile data structures, and how it delivers blazing-fast performance for caching, real-time analytics, and more.