Deep In Memory Architectures For Machine Learning
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Deep In-memory Architectures for Machine Learning
| Author | : Mingu Kang |
| Publisher | : Springer Nature |
| Total Pages | : 181 |
| Release | : 2020-01-30 |
| Genre | : Technology & Engineering |
| ISBN | : 3030359719 |
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This book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware.
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