Supply Chain Aware Computer Architecture
August Ning, Georgios Tziantzioulis, David Wentzlaff
Abstract
Progressively and increasingly, our society has become more and more dependent on semiconductors and semiconductor-enabled products and services. The importance of chips and their supply chains has been highlighted during the 2020-present chip shortage caused by manufacturing disruptions and increased demand due to the COVID-19 pandemic. However, semiconductor supply chains are inherently vulnerable to disruptions and chip crises can easily recur in the future.
We present the first work that elevates supply chain conditions to be a first-class design constraint for future computer architectures. We characterize and model the chip creation process from standard tapeout to packaging to provide a framework for architects to quickly assess the time-to-market of their chips depending on their architecture and the current market conditions. In addition, we propose a novel metric, the Chip Agility Score (𝑪𝑨𝑺) -a way to quantify a chip architecture's resilience against production-side supply changes.
We utilize our proposed time-to-market model, 𝑪𝑨𝑺, and chip design/manufacturing economic models to evaluate prominent architectures in the context of current and speculative supply chain changes. We find that using an older process node to re-release chips can decrease time-to-market by 73%-116% compared to using the most advanced processes. Also, mixed-process chiplet architectures can be 24%-51% more agile compared to equivalent single-process chiplet and monolithic designs respectively. Guided by our framework, we present an architectural design methodology that minimizes time-to-market and chip creation costs while maximizing agility for mass-produced legacy node chips.
Our modeling framework and data sets are open-sourced to advance supply chain aware computer architecture research. https://github.com/PrincetonUniversity/ttm-cas
• Hardware → Economics of chip design and manufacturing; VLSI design manufacturing considerations; • Computer systems organization → Architectures.
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Cited by top-tier papers5
- LLMCompass: Enabling Efficient Hardware Design for Large Language Model InferenceHengrui Zhang, August Ning, Rohan Baskar Prabhakar, David WentzlaffISCA 2024 · 58 citations
- ECO-CHIP: Estimation of Carbon Footprint of Chiplet-based Architectures for Sustainable VLSIChetan Choppali Sudarshan, Nikhil Matkar, Sarma B. K. Vrudhula, Sachin S. Sapatnekar et al.HPCA 2024 · 54 citations
- PIM Is All You Need: A CXL-Enabled GPU-Free System for Large Language Model InferenceYufeng Gu, Alireza Khadem, Sumanth Umesh, Ning Liang et al.ASPLOS 2025 · 44 citations
- Convivial Fabrication: Towards Relational Computational Tools For and From Craft PracticesRitik Batra, Roy Zunder, Amy Cheatle, Amritansh Kwatra et al.CHI 2026 · 3 citations
- Chip Architectures Under Advanced Computing Sanctions✱August Ning, David WentzlaffISCA 2025 · 1 citation
Builds on3
- ACT: designing sustainable computer systems with an architectural carbon modeling toolUdit Gupta, Mariam Elgamal, Gage Hills, Gu-Yeon Wei et al.ISCA 2022 · 176 citations
- BYOC: A "Bring Your Own Core" Framework for Heterogeneous-ISA ResearchJonathan Balkind, Katie Lim, Michael Schaffner, Fei Gao et al.ASPLOS 2020 · 29 citations
- SMAPPIC: Scalable Multi-FPGA Architecture Prototype Platform in the CloudGrigory Chirkov, David WentzlaffASPLOS 2023 · 13 citations
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