Processing-in-Memory for AI From Circuits to Systems /
Processing-in-Memory for AI From Circuits to Systems / [electronic resource] :
edited by Joo-Young Kim, Bongjin Kim, Tony Tae-Hyoung Kim.
- 1st ed. 2023.
- V, 165 p. 134 illus., 99 illus. in color. online resource.
Acceso multiusuario
Introduction -- Background -- PIM Constraints and Approaches -- SRAM based PIM -- DRAM based PIM -- ReRAM based PIM -- PIM for AI Training -- PIM Systems -- Conclusion.
This book provides a comprehensive introduction to processing-in-memory (PIM) technology, from its architectures to circuits implementations on multiple memory types and describes how it can be a viable computer architecture in the era of AI and big data. The authors summarize the challenges of AI hardware systems, processing-in-memory (PIM) constraints and approaches to derive system-level requirements for a practical and feasible PIM solution. The presentation focuses on feasible PIM solutions that can be implemented and used in real systems, including architectures, circuits, and implementation cases for each major memory type (SRAM, DRAM, and ReRAM). Provides first book that describes the processing-in-memory (PIM) technology thoroughly from architectures to circuits; Describes architectures, circuits, and implementation cases for each major memory type (SRAM, DRAM, and ReRAM); Focuses on feasible PIM solutions that can be implemented and used in real systems.
9783030987817
Electronic circuits.
Microprocessors.
Computer architecture.
Machine learning.
Electronic Circuits and Systems.
Processor Architectures.
Machine Learning.
TK7867-7867.5
621.3815
Acceso multiusuario
Introduction -- Background -- PIM Constraints and Approaches -- SRAM based PIM -- DRAM based PIM -- ReRAM based PIM -- PIM for AI Training -- PIM Systems -- Conclusion.
This book provides a comprehensive introduction to processing-in-memory (PIM) technology, from its architectures to circuits implementations on multiple memory types and describes how it can be a viable computer architecture in the era of AI and big data. The authors summarize the challenges of AI hardware systems, processing-in-memory (PIM) constraints and approaches to derive system-level requirements for a practical and feasible PIM solution. The presentation focuses on feasible PIM solutions that can be implemented and used in real systems, including architectures, circuits, and implementation cases for each major memory type (SRAM, DRAM, and ReRAM). Provides first book that describes the processing-in-memory (PIM) technology thoroughly from architectures to circuits; Describes architectures, circuits, and implementation cases for each major memory type (SRAM, DRAM, and ReRAM); Focuses on feasible PIM solutions that can be implemented and used in real systems.
9783030987817
Electronic circuits.
Microprocessors.
Computer architecture.
Machine learning.
Electronic Circuits and Systems.
Processor Architectures.
Machine Learning.
TK7867-7867.5
621.3815
