Architecture 2.0 Workshop

About the Workshop

The Architecture 2.0 workshop brings together researchers and practitioners exploring the intersection of artificial intelligence and computer systems. As AI continues to transform how we design, optimize, and evaluate computing systems, this workshop provides a venue for presenting cutting-edge research and fostering collaboration across the hardware stack.

The workshop focuses on AI for Systems Design, spanning computer architecture, programming languages, and operating systems. We aim to bring together researchers and practitioners applying AI techniques to systems challenges, providing a platform for work-in-progress and completed research that advances the state of the art or opens new directions for AI-driven systems research.

The workshop consists of two separate components: a Competition for students to create architecture and systems questions for evaluating and developing AI systems agents and a Call for Papers for research submissions. Both are part of the same workshop event.

Note: Research paper submissions are closed. Accepted papers are available on OpenReview.

Additional Note: The competition submission deadline has been extended to March 18, 2026 (AoE).

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Date

Monday, March 23, 2026

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Location

ASPLOS 2026 · Pittsburgh, PA

Workshop Schedule

7:00–8:00

Coffee and Registration

8:00–8:15

Welcome and Logistics

8:15-9:00

Architecture 2.0 Introduction [slides]

Andy Cheng and Arya Tschand, Harvard University

9:00–9:15

Quick Break

9:15–10:00

Traditional ML / Lightweight Models

Lightweight AI for Efficient Resource Management in Heterogeneous-Core Architectures [paper] [slides] Joshua Kim, Chaojie Zhang, Íñigo Goiri, Christopher Rossbach, Jovan Stojkovic
CEO: A Causal Evaluation and Optimization Framework for Datacenter Management Policies [paper] [slides] William Meng, Benjamin Lee, Yi Ding, Tianyi Wu
Closed-Loop Online Inference Assurance for Cyber-Physical Systems with Neural Network Controllers [paper] Yufeng Yang, Mengyu Liu

10:00–10:30

Coffee Break

10:30–11:15

Keynote Address 1: Enabling AI-driven Full-Stack Co-Optimization of Distributed AI Systems for the Architecture 2.0 era

Tushar Krishna, Georgia Tech

11:15–11:30

Quick Break

11:30–12:00

LLM Agents Part 1

A Multi-Agent-Assisted SoC Generation Methodology Leveraging Open-Source Hardware [paper] [slides] Zhuolin Li, Zhantong Zhu, Han Liu, Tianyu Jia
AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization [paper] [slides] Genghan Zhang, Shaowei Zhu, Anjiang Wei, Zhenyu Song, Allen Nie, Zhen Jia, Nandita Vijaykumar, Yida Wang, Kunle Olukotun

12:00–1:30

Lunch

1:30–2:15

Keynote Address 2: The New Golden Edge for the Computer Architect [slides]

We are often told that we are in a golden age for computer architecture, but this moment is something more profound: a golden age for the computer architect. Advances in AI are collapsing the traditional boundaries between architecture, software, and hardware implementation, enabling architects to move from idea to realization across the full stack. Yet, despite this promise, today’s AI systems still struggle to reason about architectural design due to missing abstractions and outdated tooling. In this talk, I will argue that the next era of innovation is not just about better hardware, but about redefining how we design systems: introducing new machine-understandable abstractions, building AI-native tools, and embracing system-level thinking in a world of increasingly specialized and heterogeneous architectures. As AI workloads diversify and hardware fragments, the role of the architect expands—from optimizing components to defining design spaces, composing systems, and shaping the software–hardware interface. This is not just a technological shift, but a redefinition of what it means to be a computer architect. Yakun Sophia Shao, UC Berkeley

2:15–2:30

Quick Break

2:30–3:30

LLM Agents Part 2

ArchAgent: Towards Agentic Architecture Discovery [paper] Raghav Gupta, Akanksha Jain, Borivoje Nikolic, Parthasarathy Ranganathan, Sagar Karandikar
EggMind: LLM-Driven Two-Dimensional Intelligence for Scalable Equality Saturation [paper] [slides] Youwei Xiao, Chenyun Yin, Yun Liang
AC Loop: An LLM-Based End-to-End Auto Calibration Framework [paper] Hao Zhen, Qingxuan Kang, Yungang Bao, Trevor E. Carlson
LLM-Augmented FPGA Timing Closure: Toward Intelligent Static Timing Analysis Agents [paper] [slides] Saher Elsayed

3:30–4:00

Coffee Break

4:00–5:00

Wacky Ideas / Proposals

The Case for Uncertainty-Governed Predictor Hierarchies in ML for Systems [paper] Christos Zarkos, Nevena Stojkovic, Varun Gohil, Christina Delimitrou
Cloning the Unshareable: Agentic AI for Synthesizing Open, Production-Faithful Datacenter Benchmarks [paper] [slides] Alan Andrade, Petar Acimovic, Wei Su, Jovan Stojkovic
Hunting for Offload: Automated Discovery of Acceleratable Code in Datacenters [paper] [slides] Joshua Kim, Chaojie Zhang, Íñigo Goiri, Christopher Rossbach, Jovan Stojkovic
Multi-Agent Memory from a Computer Architecture Perspective: Visions and Challenges Ahead [paper] Zhongming Yu, Naicheng Yu, Hejia Zhang, Wentao Ni, Yin Mingrui, Jiaying Yang, Yujie Zhao, Jishen Zhao

5:00–5:15

Quick Break

5:15–6:00

Roundtable Discussion

QuArch Architecture & Systems Competition

This competition is sponsored by

Note: Competition submissions are closed; however the QuArch dataset is still accepting submissions here.

We invite students to participate in the QuArch Architecture & Systems Competition, which focuses on creating high-quality questions that evaluate reasoning in the core displines of ASPLOS: computer architecture, programming languages, compilers, and operating systems. The goal of this competition is to assess and advance the ability of AI systems to reason about real-world systems concepts that span computer architecture, programming languages, compilers, and operating systems.

🏆 Competition winners

🥇 Mahnoor Malik (NED University of Technology)
🥈 User “hexu” (Advanced Computing SIG)
🥉 Gokulan Ravi (Purdue University)

🏆 About the Competition

Objective:

Participants will submit original questions designed to probe understanding, analysis, and reasoning in computer architecture and related systems domains. Questions may target conceptual knowledge, design trade-offs, performance analysis, or optimization challenges.

All questions should be suitable for evaluating an AI system’s architectural reasoning capabilities and should challenge and evaluate such capabilities.

Evaluation:

A committee will review submissions and select winners based on:

Quality & difficulty
Creativity & relevance
Depth & quantity

Tip: We encourage questions that reflect realistic architectural scenarios, modern hardware platforms, and emerging systems challenges.

Both exploratory and polished submissions are welcome. No prior competition experience is required!

🏆 Awards

Winners will be recognized with cash prizes, with the potential for additional physical awards.

📚 Resources

For more information and submission details, visit the QuArch website or read the QuArch paper.

Additional links and references are collected in the Resources section below.

📅 Timeline

Submission Deadline: ~~March 7, 2026~~ March 18, 2026 (AoE)
Winners Announcement: March 23, 2026 (at the workshop)

Submit Questions

Call for Papers: AI for Systems Design

Note: Submissions closed. View accepted papers on OpenReview.

We invite submissions that explore the use of artificial intelligence to design, analyze, optimize, or evaluate computer systems. The workshop aims to bring together researchers and practitioners applying AI techniques to systems challenges across the hardware stack.

We welcome both work-in-progress and completed research that advances the state of the art or opens new directions for AI-driven systems research.

Note: The workshop will not have formal proceedings, and authors are free to publish extended versions of their work in other conferences and journals.

Submission Type

We welcome works of three different formats to the workshop:

Early/Work-in-Progress Research (4 Pages)
Extended Abstract of Completed Research (2 Pages, with pointer to full-length paper)
Position/Opinion Papers (2 Pages)

Topics of Interest

Submissions should focus on AI for Systems, spanning computer architecture, programming languages, and operating systems, including but not limited to the following areas:

Computer Architecture

AI-driven microarchitecture design, tuning, and exploration
Learning-based design space exploration and architectural trade-off analysis
Processor, accelerator, and heterogeneous system design
GPU, TPU, and accelerator architectures and kernel optimization
Memory systems, cache hierarchies, interconnects, and storage optimization using AI
Learning-based performance, power, energy, and reliability modeling
Surrogate models to accelerate architectural simulation and evaluation
AI methods for identifying architectural bottlenecks and inefficiencies

Programming Languages and Compilers

AI-assisted compiler optimization and code generation
Learning-based cost models for compiler and runtime decisions
Automatic kernel transformation, scheduling, and tuning
Program analysis and optimization using machine learning
Cross-layer optimization between compilers, runtimes, and hardware
Domain-specific languages (DSLs) and abstractions enabled by AI

Operating Systems and Runtime Systems

AI-driven scheduling, resource management, and system optimization
Learning-based memory management, caching, and I/O policies
Intelligent runtime systems for heterogeneous and accelerator-rich platforms
Performance modeling and prediction for OS and runtime decisions
AI for system monitoring, diagnosis, and anomaly detection
Co-design of OS policies with hardware and compiler support

We also welcome contributions on datasets, benchmarks, and open-source infrastructure that enable or evaluate AI-driven approaches across the architecture–language–OS stack.

Reviewing Details

Submission and Platform: All submissions will be handled through the OpenReview platform. The review process will be single-blind; therefore, submissions should include author names and affiliations and should not be anonymized.

Decisions: All accept/reject decisions will be made exclusively by the human members of the organizing committee. Submissions will be evaluated for relevance to the workshop theme, technical novelty, and clarity of presentation.

AI-Assisted Feedback: In alignment with the workshop's focus on leveraging AI, the organizing committee will pilot ArchScholar, an AI-based review assistant that is custom-built on Archipedia: a corpus of computer architecture and systems literature spanning 50 years. This tool will be used to generate preliminary written feedback and reviews, which will be publicly posted on OpenReview. Importantly, the AI-assisted tool is used solely to support the review process and to provide individualized written feedback to authors; it does not determine final decisions. We welcome feedback from the community and hope to encourage thoughtful, constructive discussion around the use of AI-assisted reviewing as part of the workshop.

Submission Details

Submission deadline (passed): ~~February 12, 2026~~ February 19, 2026 (AoE)

Author Notification: ~~February 17, 2026~~ February 24, 2026

Paper length:

Early/Work-in-Progress Research: 4 pages
Extended Abstract of Completed Research: 2 pages (with pointer to full-length paper)
Position/Opinion Papers: 2 pages

(Page counts exclude references and appendix)

Format: Standard ASPLOS 2026 Latex Template

View accepted papers (OpenReview)