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Nandakumar, S. et al. Mixed-precision architecture based on computational memory for training deep neural networks.
In that case, semantic memory for arithmetic but not non-arithmetical facts was impaired.
This decreases computational memory needed for assembly without losing valuable biological information.
In-memory computing is a promising approach in which nanoscale resistive memory devices, organized in a computational memory unit, are used for both processing and memory.
The left AG is assumed to support the long term memory retrieval for arithmetic fact knowledge [ 20].
The left AG is assumed to subserve the long term memory retrieval for arithmetic fact knowledge (e.g., multiplication tables) [ 8].
Thus, this method can reduce computational time and memory for storing matrix coefficients.
A basis for area-time design decisions for arithmetic and memory operations is formulated from a study of computationally intensive programs.
This still requires no run-time memory or arithmetic computations on the part of the robots.
The ALU has several to more than a hundred registers that temporarily hold results of its computations for further arithmetic operations or for transfer to main memory.
This representation is the primary code for accessing a rote verbal memory of arithmetic facts (e.g., "three times five, fifteen").
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