Compute Library — Index
Software engineering + computer-science substance: distributed systems, databases, operating systems, networking, ML/AI fundamentals, security, observability. Sister library to
Engineering/(hardware + physics) andLanguages/(the syntactic catalog).
- Status: Tier 1 complete (2026-05-16). 20 deep notes.
- Library structure: mirrors Engineering / Robotics / Languages — Tier 1 deep notes + Tier 2 specialty + Tier 3 family indexes.
- Schema: see _schema (TBD)
Subdomains
| Subdomain | Examples |
|---|---|
| Distributed systems | consensus (Raft/Paxos), CAP, replication, sharding, gossip, leader election |
| Databases | OLTP, OLAP, key-value, document, columnar, graph, time-series, vector |
| Operating systems | process / threads / scheduling, memory management, virtual memory, IPC, kernels |
| Networking | TCP/IP, UDP, HTTP/2/3, QUIC, DNS, BGP, mesh, gRPC, WebSocket |
| Concurrency | threads, async, actors, CSP, locks, lock-free, transactional memory |
| Compilers + runtimes | parsing, IR, JIT, AOT, GC, type systems |
| ML / AI | transformers, fine-tuning, RAG, embeddings, training, inference, evaluation |
| Cloud / cloud-native | containers, K8s, serverless, IaC, service mesh, CD/CD |
| Observability | metrics (Prometheus), logs, traces (OTel), profiling |
| Security | crypto, auth (OAuth/OIDC/SAML), TLS, secrets, RBAC, attack patterns |
| Performance engineering | profiling, benchmarking, latency, throughput, cache hierarchy |
| Architecture | microservices, monolith, event-driven, CQRS, hexagonal |
Tier 1 — Complete (20 / 20, 2026-05-16)
| Status | Topic | File | Lines | Subdomain |
|---|---|---|---|---|
| ✅ | Distributed systems fundamentals | distributed-systems-fundamentals | 584 | distributed-systems |
| ✅ | Consensus protocols | consensus-protocols | 490 | distributed-systems |
| ✅ | Database internals | database-internals | 812 | databases |
| ✅ | SQL vs NoSQL design | sql-nosql-design | 564 | databases |
| ✅ | OS scheduling, memory & IPC | os-scheduling-memory | 586 | operating-systems |
| ✅ | Networking foundations | networking-foundations | 605 | networking |
| ✅ | HTTP/2, HTTP/3 & QUIC deep | http2-http3-quic | 520 | networking |
| ✅ | Concurrency primitives | concurrency-primitives | 588 | concurrency |
| ✅ | Compiler design | compiler-design | 592 | compilers |
| ✅ | Garbage collection | garbage-collection | 540 | runtimes |
| ✅ | Transformer architecture | transformer-architecture | 591 | ml-ai |
| ✅ | Fine-tuning & RLHF | fine-tuning-rlhf | 896 | ml-ai |
| ✅ | RAG, embeddings, vector search | rag-embeddings-vector-search | 432 | ml-ai |
| ✅ | LLM inference optimization | inference-optimization | 566 | ml-ai |
| ✅ | Kubernetes deep | kubernetes-deep | 595 | cloud-native |
| ✅ | Containers & service mesh | containers-service-mesh | 593 | cloud-native |
| ✅ | Observability stack | observability-stack | 580 | observability |
| ✅ | Cryptography fundamentals | cryptography-fundamentals | 1096 | security |
| ✅ | Authentication & authorization | auth-authz | 772 | security |
| ✅ | CPU cache & performance | cpu-cache-performance | 506 | performance |
| ✅ | Microservices patterns | microservices-patterns | 552 | architecture |
🎯 Compute Tier 1 complete: 21 / 21 deep notes, ~12,460 lines.
Tier 2 — Specialty (in progress)
| Topic | File |
|---|---|
| Compilers & program analysis | compilers-and-program-analysis |
| Databases internals (deep) | databases-internals-deep |
| Differential privacy & privacy tech | differential-privacy-and-privacy-tech |
| Distributed systems (deep) | distributed-systems-deep |
| FPGA & hardware acceleration | fpga-and-hardware-acceleration |
Planned: Raft implementation details, BTrees vs LSM trees (now partly covered in databases-internals-deep), CRDTs, FRP, RDMA + DPDK, eBPF, GPU programming (CUDA + HIP + Triton), TPU + accelerators, model serving (vLLM / TGI), agent systems.
Tier 3 — Family indexes (deferred)
- Database engine taxonomy (Postgres, MySQL, MongoDB, Cassandra, ClickHouse, DuckDB, etc.)
- Cloud provider service mapping (AWS / GCP / Azure)
- ML framework comparison (PyTorch / JAX / TF / Keras)
- LLM landscape (open / closed model catalog)
- Container orchestrators (K8s / Nomad / ECS)
- Observability tools (Prometheus / Grafana / Datadog / Honeycomb)
- Auth providers (Auth0 / Clerk / WorkOS / Stytch)
- Languages-vs-runtimes catalog
Adjacent libraries
- Engineering — physical disciplines (hardware that runs the compute)
- Robotics — applied robotics (uses compute for perception + planning + control)
- Languages — language syntactic + library catalog
- Math — mathematics + statistics (underlies ML + algorithms)
How to study this library
- Learning paths — _learn_next — “if you’ve read X, learn Y next” recommendation graph plus five named multi-step tracks (Distributed-systems engineer, Database engineer, ML platform engineer, Cloud-native SRE, Security engineer).
- Cross-cutting comparisons — two
_compare_*notes that span the library: _compare_consistency_models, _compare_service-architectures.
How to use
For a software-engineering question:
- Identify the subdomain (distributed / DB / OS / network / concurrency / ML / cloud / security / observability / arch).
- Read the relevant Tier 1 deep note.
- Use Tier 3 family indexes to find specific tool/product options.
- Cross-reference Languages for syntactic / library detail.
- Cross-reference Math for theoretical foundations (probability, complexity, linear algebra, info theory).