Coder-kung-fu is an educational resource collection that teaches fundamental computer architecture and systems knowledge through deep technical analysis.
The project addresses the need for developers to understand how kernels, hardware, and system components actually work at a foundational level. It organizes this knowledge into four core modules covering CPU, memory, disk, and network subsystems. Rather than providing shallow overviews, the material dives into architectural details, performance characteristics, and the evolution of hardware designs over time. Topics range from CPU cache behavior and memory alignment to GPU architecture evolution and server hardware specifications.
This resource suits developers who want to move beyond surface-level understanding and build genuine expertise in systems programming and performance optimization. It works best for those preparing for senior engineering roles or working on performance-critical systems where understanding hardware constraints directly impacts design decisions. The collection complements formal study with practical insights into real hardware behavior, such as how to measure TLB misses or interpret server memory configurations using system tools.
The project maintains an active publication schedule with regular deep-dive articles on emerging topics, including recent coverage of GPU architecture evolution across multiple NVIDIA generations. Content updates appear consistently with new technical analyses being added to the repository. The material reflects sustained engagement with contemporary hardware developments rather than static documentation, suggesting ongoing effort to keep the knowledge current as processor and memory technologies advance.
