Kim et al., 2021 - Google Patents
Z-PIM: A sparsity-aware processing-in-memory architecture with fully variable weight bit-precision for energy-efficient deep neural networksKim et al., 2021
- Document ID
- 8311222323236518641
- Author
- Kim J
- Lee J
- Lee J
- Heo J
- Kim J
- Publication year
- Publication venue
- IEEE Journal of Solid-State Circuits
External Links
Snippet
We present an energy-efficient processing-in-memory (PIM) architecture named Z-PIM that supports both sparsity handling and fully variable bit-precision in weight data for energy- efficient deep neural networks. Z-PIM adopts the bit-serial arithmetic that performs a …
- 230000001537 neural 0 title abstract description 16
Classifications
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- G06F7/52—Multiplying; Dividing
- G06F7/523—Multiplying only
- G06F7/53—Multiplying only in parallel-parallel fashion, i.e. both operands being entered in parallel
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- G06F9/30007—Arrangements for executing specific machine instructions to perform operations on data operands
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- G06F17/5009—Computer-aided design using simulation
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- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
- G06F7/38—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation
- G06F7/48—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices
- G06F7/544—Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using non-contact-making devices, e.g. tube, solid state device; using unspecified devices for evaluating functions by calculation
- G06F7/5443—Sum of products
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- G—PHYSICS
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- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
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- G06F15/00—Digital computers in general; Data processing equipment in general
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- G06F15/80—Architectures of general purpose stored programme computers comprising an array of processing units with common control, e.g. single instruction multiple data processors
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