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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).
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).
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