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It is shown that semantic understanding and reasoning about a program is a vital component in inserting effective software prefetches, and that prefetching at the scale of large codebases poses new challenges, including prefetch codependence and interference.
The introduction of ScientistTwo, a fully autonomous multi-agent framework designed to realize problem-driven autonomous research, and its results show that ScientistTwo is not merely an assistive tool but an autonomous scientific pioneer capable of pushing the frontiers of human discovery.
SMART is described, a rigorous symbolic performance-modeling library for ML systems whose main branch contains almost no code, and Regenerated implementations reproduce hand-audited reference models to round-off precision, suggesting that design docs can be the durable artifact for ML-systems co-design tools.
This work presents ArchAgent v2, a framework which scales automated microarchitecture search to multi-level data prefetching and introduces two new additions to ArchAgent: a cascaded evolutionary search that subdivides the design space by sequentially evolving and freezing prefetchers at individual cache levels, and a...
Themis is a profile-guided hardware prefetching solution that implements a novel hardware-software interface for data prefetching: the software directs the hardware on where to prefetch, and the hardware identifies and issues prefetches in the regions of interest.
It is shown that solving systems problems such as resource scheduling and code optimization requires reasoning that is fundamentally as hard as any reasoning problem a human might have to solve, which makes systems problems a promising target for AGI research, and that both the AI and systems community should investiga...
AI-generated C++ code has a distinct quality profile, showing higher rates of interface and coupling burdens, copy and allocation overheads, and a reliance on explicit loops over optimized standard APIs, which translates into tangible downstream costs, including increased review effort and a 5-8% increase in compute re...
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