TY - GEN
T1 - Supply Chain Aware Computer Architecture
AU - Tziantzioulis, Georgios
AU - Ning, August
AU - Wentzlaff, David
N1 - Funding Information:
We would like to thank Grigory Chirkov, Marcelo Orenes-Vera, Rohan Prabhakar, as well as the entire Princeton Parallel Group, and our anonymous reviewers for their feedback, suggestions, and encouragement. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-2039656, the National Science Foundation under Grant No. CNS-1823222, Air Force Research Laboratory (AFRL) and Defense Advanced Research Projects Agency (DARPA) under agreement No. FA8650-18-2-7862. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory (AFRL) and Defense Advanced Research Projects Agency (DARPA) or the U.S. Government.
Publisher Copyright:
© 2023 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 2023/6/17
Y1 - 2023/6/17
N2 - 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.
AB - 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.
KW - chip shortage
KW - economics
KW - modeling
KW - semiconductor supply chain
UR - http://www.scopus.com/inward/record.url?scp=85164021121&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85164021121&partnerID=8YFLogxK
U2 - 10.1145/3579371.3589052
DO - 10.1145/3579371.3589052
M3 - Conference contribution
AN - SCOPUS:85164021121
T3 - Proceedings - International Symposium on Computer Architecture
SP - 230
EP - 244
BT - ISCA 2023 - Proceedings of the 2023 50th Annual International Symposium on Computer Architecture
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 50th Annual International Symposium on Computer Architecture, ISCA 2023
Y2 - 17 June 2023 through 21 June 2023
ER -