CS249r Notes: What We Learned

Weekly recaps and reflections from Harvard’s CS249r: Architecture 2.0


Week 5: From CPU Transparency to GPU Complexity - The Performance Engineering Frontier

October 01, 2024 • Software, performance • 24 min read

Over the past four weeks, we’ve been exploring a central question: can AI systems help us optimize performance at scale? We started with the foundational challenges of Architecture 2.0, examined the software engineering reality gap between AI capabilities and real development tasks, and investigated how Google’s ECO system tackles CPU...

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Week 3: The Software Engineering Reality Gap

September 17, 2024 • Software • 16 min read

As we were teaching class this very Wednesday, September 17th, news broke that Google DeepMind’s Gemini achieved gold medal level performance at the 2025 International Collegiate Programming Contest (ICPC) World Finals, solving 10 of 12 complex algorithmic problems in the world’s most prestigious competitive programming competition.Gemini’s ICPC performance builds on...

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Week 2: The Fundamental Challenges Nobody Talks About

September 08, 2024 • Architecture • 13 min read

Here’s what nobody tells you about applying AI to computer architecture: it’s not just harder than other domains—it’s fundamentally different in ways that make most AI success stories irrelevant. This week, we confronted why the techniques that conquered vision, language, and games stumble when faced with cache hierarchies and instruction...

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Week 1: The End of an Era, The Dawn of Architecture 2.0

September 03, 2024 • Architecture • 11 min read

Moore’s Law is dying. Dennard scaling ended years ago.Dennard scaling, formulated by Robert Dennard at IBM in 1974, observed that as transistors became smaller, their switching voltage and current could be reduced proportionally, keeping power density roughly constant. This meant each new generation delivered faster processors without exponentially increasing power...

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