Editors:
Tianyin Xu, Akshitha Sriraman, Baris Kasikci, and Dong Du
LDOS: Toward A Learning-Directed Operating System
Editors’ note: LDOS (Learning Directed Operating System) is among the most exciting expedition projects that showcase how AI could help revamp policies and mechanisms of modern operating systems (arguably the most important systems software). In this article (the fifth blog in The Next Horizon of System Intelligence series), the LDOS team shares their vision, roadmap, and
Let the Barbarians In: How AI Can Accelerate Systems Performance Research
Editors’ note: You must remember the widely discussed Barbarians at The Gate article that opened the The Next Horizon of System Intelligence series! For the fourth blog, we welcome back the ADRS team from UC Berkeley to share their recent work that demonstrates how to embrace and utilize AI (as the “barbarians”) to accelerate system performance
Glia: A Human-Inspired AI for Systems Design and Optimization
Editors’ note: For the third The Next Horizon of System Intelligence series, we invited the Glia team from MIT to share their work on developing human-inspired AI for system design and optimizations. The last blog article defined the ladder of System Intelligence based on the learning experience of PhD students and Glia is such a PhD-level
Defining System Intelligence
Editors’ note. For the second article of the The Next Horizon of System Intelligence series, the team from Microsoft Research and University of Illinois Urbana Champaign shares their efforts on defining System Intelligence and their perspective on realizing it through benchmarks as an initial foundation. They are calling for community contributions to enrich existing benchmarks and create
From Theory to Practice: Introducing Architectural Prisms, an Experiment in AI-First Academic Dialogue
Editor’s notes: This article is cross-referenced from the SIGARCH Blog. The problem described in the article also applies to the SIGOPS community. Certainly, whether to ask AI for help in the paper review systems should be a community decision and must be done in the right way. A little while ago, I published a post
Wafer-Scale AI Compute: A System Software Perspective
This article originally appeared in USENIX ;login: magazine, shepherded by Rik Farrow. As AI models grow larger and more complex, traditional computing architectures are hitting performance and efficiency limits. A new class of hardware, wafer-scale AI chips, pushes these boundaries by integrating hundreds of thousands of cores and massive on-chip memory onto a single wafer.