30 PyTorch problems cover MLSys inference, quantization, KV cache, and batching
kalyan_kpl · x · 2026-07-23
A 30-problem PyTorch sheet for learning MLSys and inference, covering attention variants, MoE, quantization, KV cache, decoding, batching, and distributed inference systems.
The sheet is organized into sections and is meant as a hands-on study aid rather than a tutorial blog post. The accompanying image shows the full curriculum, including attention architectures, efficient transformer components, serving schedulers, and distributed inference topics.
More from coding & agent
- Bindu Reddy tests an AI brain with long-term memory on his own work — bindureddy · 2026-07-23
- GPT-5.6 reads the code while Fable 5 keeps probing MCP calls until it works — Angaisb_ · 2026-07-23
- Claude Code budget checker reads local logs and warns before agents burn through limits — getnable · 2026-07-23
- Open-source WeChat Channels download Skill lets users save videos by URL — vista8 · 2026-07-23
- Fleet engineering turns vibe coding into parallel AI coding sessions — victor_explore · 2026-07-23
- Open repo packages 21 chapters of agentic design patterns with code notebooks — tom_doerr · 2026-07-23