AgentDSE uses an LLM agent in a simulator-in-the-loop setup to achieve competitive or superior architectural designs with up to 100x fewer evaluations than traditional black-box optimization methods.
ArchAgent: Agentic AI-driven Computer Architecture Discovery, February 2026.https://arxiv.org/abs/2602.22425
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Evolutionary coding agents achieve most benchmark gains through a small subset of edit types and by cycling previously deleted code lines rather than developing new algorithmic structures.
CHIA is a distributed graph-based framework for composing, deploying, and verifying agentic AI hardware/software co-design flows, demonstrated on RTL, simulation, and compiler tasks.
An LLM-driven agentic system evolves microarchitectural policies for cache replacement, data prefetching, and branch prediction, producing designs that match or exceed prior state-of-the-art in IPC on standard benchmarks.
citing papers explorer
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AgentDSE: Reasoning-Augmented Architectural Design Space Exploration
AgentDSE uses an LLM agent in a simulator-in-the-loop setup to achieve competitive or superior architectural designs with up to 100x fewer evaluations than traditional black-box optimization methods.
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What Do Evolutionary Coding Agents Evolve?
Evolutionary coding agents achieve most benchmark gains through a small subset of edit types and by cycling previously deleted code lines rather than developing new algorithmic structures.
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CHIA: An open-source framework for principled, agentic AI-driven hardware/software co-design research
CHIA is a distributed graph-based framework for composing, deploying, and verifying agentic AI hardware/software co-design flows, demonstrated on RTL, simulation, and compiler tasks.
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Agentic Architect: An Agentic AI Framework for Architecture Design Exploration and Optimization
An LLM-driven agentic system evolves microarchitectural policies for cache replacement, data prefetching, and branch prediction, producing designs that match or exceed prior state-of-the-art in IPC on standard benchmarks.