QuArch: A Question-Answering Dataset for AI Agents in Computer Architecture

IF 1.4 3区 计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Shvetank Prakash;Andrew Cheng;Jason Yik;Arya Tschand;Radhika Ghosal;Ikechukwu Uchendu;Jessica Quaye;Jeffrey Ma;Shreyas Grampurohit;Sofia Giannuzzi;Arnav Balyan;Fin Amin;Aadya Pipersenia;Yash Choudhary;Ankita Nayak;Amir Yazdanbakhsh;Vijay Janapa Reddi
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Abstract

We introduce QuArch, a dataset of 1500 human-validated question-answer pairs designed to evaluate and enhance language models’ understanding of computer architecture. The dataset covers areas including processor design, memory systems, and performance optimization. Our analysis highlights a significant performance gap: the best closed-source model achieves 84% accuracy, while the top small open-source model reaches 72%. We observe notable struggles on QAs regarding memory systems and interconnection networks. Fine-tuning with QuArch improves small model accuracy by up to 8%, establishing a foundation for advancing AI-driven computer architecture research. The dataset and the leaderboard are accessible at https://quarch.ai/.
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来源期刊
IEEE Computer Architecture Letters
IEEE Computer Architecture Letters COMPUTER SCIENCE, HARDWARE & ARCHITECTURE-
CiteScore
4.60
自引率
4.30%
发文量
29
期刊介绍: IEEE Computer Architecture Letters is a rigorously peer-reviewed forum for publishing early, high-impact results in the areas of uni- and multiprocessor computer systems, computer architecture, microarchitecture, workload characterization, performance evaluation and simulation techniques, and power-aware computing. Submissions are welcomed on any topic in computer architecture, especially but not limited to: microprocessor and multiprocessor systems, microarchitecture and ILP processors, workload characterization, performance evaluation and simulation techniques, compiler-hardware and operating system-hardware interactions, interconnect architectures, memory and cache systems, power and thermal issues at the architecture level, I/O architectures and techniques, independent validation of previously published results, analysis of unsuccessful techniques, domain-specific processor architectures (e.g., embedded, graphics, network, etc.), real-time and high-availability architectures, reconfigurable systems.
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