performance-optimization

Squeezing more throughput, lower latency, and reduced compute cost from AI systems and the software supporting them. This tag covers profiling, compiler-level tuning, and architectural decisions that make code faster and cheaper without sacrificing correctness. Practical topics include AI-assisted optimization loops, hardware-specific instruction tuning, inference efficiency, and surfacing the hidden waste already embedded in mature, production codebases.

Vast dark silicon landscape with nearly all CPU cores dormant, visualizing wasted compute sitting idle in existing hardware.

ai-code-optimization, performance-optimization, emulation, snes9x, software-efficiency, ai-assisted-development

The Cheapest Compute on Earth Is the Compute You're Already Wasting

An AI-driven iteration loop made the Snes9x emulator 61% faster on x86-64 and 52% faster on arm64 in three days for under $30, with every frame and audio sample bit-exact against the original. The argument: the cheapest performance gain is the compute already wasted in mature code.