Glia is a multi-agent LLM architecture that autonomously designs distributed systems algorithms through agents specialized in reasoning, experimentation, and analysis. Applied to GPU cluster optimization, it generates interpretable algorithms for request routing and scheduling that match human-expert performance. The work demonstrates how structured agent workflows combining LLMs with empirical feedback can solve complex systems design problems creatively.
Research
Glia: A Human-Inspired AI for Automated Systems Design and Optimization
Glia, a multi-agent LLM system, autonomously designs distributed systems algorithms that rival human-expert solutions—demonstrated via GPU cluster request routing and scheduling optimization.
Monday, April 6, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline
Tags
research
/// RELATED
Products1d ago
ASML's Best Selling Product Isn't What You Think It Is
ASML's DIY Lego replica of its EUV lithography tool outpaces real machine sales 1,355-to-6, exposing the extreme cost barrier for critical chip-making equipment.
Research1d ago
Are Tools All We Need? Unveiling the Tool-Use Tax in LLM Agents
Research quantifies the performance overhead of tool integration in LLM agents, revealing whether the efficiency cost of tool-use is a fundamental architectural bottleneck.