Abstract: The present disclosure provides a calculation error correction device including a first learning unit that trains an effective weight value prediction model for outputting an effective weight value matrix by using learning data in response to an input of the random weight value matrix, an effective weight value calculation unit that inputs a first weight value matrix into the effective weight value prediction model to derive the effective weight value matrix, a second learning unit that applies a second input vector to a target neural network as an input value, applied the effective weight value matrix as a weight value, and trains the weight value such that an output vector follows a result of multiplication of the second input vector and the first weight value matrix, and a control unit that performs matrix-vector multiplication by mapping the first input vector and the trained weight value matrix to the resistive memory.

Abstract: Disclosed are an encoder and decoder configured to encode and decode a weight and an operating method of the encoder and the decoder. An operating method of a decoding device includes: receiving a compressed weight including a preceding code and subsequent bits following the preceding code; and decoding the compressed weight by applying the preceding code of the compressed weight to a Huffman tree, wherein the Huffman tree decodes the preceding code, and wherein the decoded preceding code is joined with the subsequent bits to form a decompressed version of the compressed weight.

Abstract: Disclosed are a method of expressing a parameter variably and an apparatus for the same. A neural processor apparatus includes: a comparator configured to read a value of a fixed-length exponent of a previously-converted parameter value and obtain mantissa-length information of a mantissa, wherein the mantissa-length information is obtained from a mapping table based on being mapped to the value of the exponent; a shifter configured to read the mantissa of the previously-converted parameter value and use the mantissa-length information to convert a structure of the previously-converted parameter value; and the mapping table, in which the mantissa-length information of the mantissa is mapped to the value of the exponent.

Abstract: A memory device includes a memory cell array, an operator comprising a logic circuit configured to perform an operation comprising a plurality of stages, and a plurality of buffers configured to store first data and second data corresponding to a plurality of operation commands received from a host for each of the plurality of stages, respectively, wherein the operator comprises a butterfly unit configured to perform butterfly operations based on at least one of the first data and the second data.

Abstract: The present disclosure provides a calculation error correction device including a first learning unit that trains an effective weight value prediction model for outputting an effective weight value matrix by using learning data in response to an input of the random weight value matrix, an effective weight value calculation unit that inputs a first weight value matrix into the effective weight value prediction model to derive the effective weight value matrix, a second learning unit that applies a second input vector to a target neural network as an input value, applied the effective weight value matrix as a weight value, and trains the weight value such that an output vector follows a result of multiplication of the second input vector and the first weight value matrix, and a control unit that performs matrix-vector multiplication by mapping the first input vector and the trained weight value matrix to the resistive memory.

Abstract: A die bonding device includes: a wafer holder supporting a wafer where a die is formed; an ejector holder disposed at the wafer holder below the wafer and supporting a die ejector that assists separating the die from the wafer; a support unit supporting a substrate where the die is to be attached; a bonding unit that picks up the die from the wafer and attaches the picked-up die to the substrate; an ejector buffer unit that receives the die ejector; and a replacing unit that transfers the die ejector between the ejector holder and the ejector buffer unit.

Abstract: A die bonding device includes: a wafer holder supporting a wafer where a die is formed; an ejector holder disposed at the wafer holder below the wafer and supporting a die ejector that assists separating the die from the wafer; a support unit supporting a substrate where the die is to be attached; a bonding unit that picks up the die from the wafer and attaches the picked-up die to the substrate; an ejector buffer unit that receives the die ejector; and a replacing unit that transfers the die ejector between the ejector holder and the ejector buffer unit.