Processing-in-Memory Development Strategy for AI Computing Using Main-Path and Doc2Vec Analyses

Euiyoung Chung and So Young Sohn ()
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Euiyoung Chung: Memory System R&D, SK Hynix America, 3101 N 1st, San Jose, CA 95134, USA
So Young Sohn: Department of Industrial Engineering, Yonsei University, Shinchon-Dong 134, Seoul 03722, Republic of Korea

Sustainability, 2023, vol. 15, issue 16, 1-15

Abstract: Processing-in-Memory (PiM), which combines a memory device with a Processing Unit (PU) into an integrated chip, has drawn special attention in the field of Artificial Intelligence semiconductors. Currently, in the development and commercialization of PiM’s technology, there are challenges in the hegemony competition between the PU and memory device industries. In addition, there are challenges in finding strategic partnerships rather than independent development due to the complexity of technological development caused by heterogeneous chips. In this study, patent Main Path Analysis (MPA) is used to identify the majority and complementary groups between PU and memory devices for PiM. Subsequently, Document-to-Vector (Doc2Vec) and similarity-scoring analyses are used to determine the potential partners for technical cooperation required for PiM technology development for the majority group identified. According to the empirical results, PiM core technology is evolving from PU to memory device with an ‘architecture-operation-architecture’ design pattern. The ten ASIC candidates are identified for strategic partnerships with memory device suppliers. Those partnership candidates include several mobile AP firms, implying PiM’s opportunities in the field of mobile applications. It suggests that memory device suppliers should prepare for different technology strategies for PiM technology development. This study contributes to the literature and high-tech industry via the proposed quantitative technology partnership model.

Keywords: main path analysis; doc2Vec; semiconductor patent; partnership; processing-in-memory; artificial intelligence (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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