Round pegs, square holes: Why GPGPUs are an architectural mismatch for modern LLMs

The saying “round pegs do not fit square holes” persists because it captures a deep engineering reality: inefficiency most often arises not from flawed components, but from misalignment between a system’s assumptions and the problem it is asked to solve. A square hole is not poorly made; it’s simply optimized for square pegs. Modern large … Read more

Why memory swizzling is hidden tax on AI compute

Walk into any modern AI lab, data center, or autonomous vehicle development environment, and you’ll hear engineers talk endlessly about FLOPS, TOPS, sparsity, quantization, and model scaling laws. Those metrics dominate headlines and product datasheets. If you spend time with the people actually building or optimizing these systems, a different truth emerges: Raw arithmetic capability … Read more

The role of AI processor architecture in power consumption efficiency

From 2005 to 2017—the pre-AI era—the electricity flowing into U.S. data centers remained remarkably stable. This was true despite the explosive demand for cloud-based services. Social networks such as Facebook, Netflix, real-time collaboration tools, online commerce, and the mobile-app ecosystem all grew at unprecedented rates. Yet continual improvements in server efficiency kept total energy consumption … Read more