Processing-in-Memory for AI [electronic resource] : From Circuits to Systems / edited by Joo-Young Kim, Bongjin Kim, Tony Tae-Hyoung Kim.

Colaborador(es): Kim, Joo-Young [editor.] | Kim, Bongjin [editor.] | Kim, Tony Tae-Hyoung [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoEditor: Cham : Springer International Publishing : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: V, 165 p. 134 illus., 99 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783030987817Tema(s): Electronic circuits | Microprocessors | Computer architecture | Machine learning | Electronic Circuits and Systems | Processor Architectures | Machine LearningFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 621.3815 Clasificación LoC:TK7867-7867.5Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Background -- PIM Constraints and Approaches -- SRAM based PIM -- DRAM based PIM -- ReRAM based PIM -- PIM for AI Training -- PIM Systems -- Conclusion.
En: Springer Nature eBookResumen: 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.
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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.

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