System and method for memory compression for deep learning networks

A system for memory compression for a deep learning network, comprising:

• a first memory having a plurality of rows each having a specified number of columns, each column having a column width;
• an input module for:
• receiving an input data stream to be processed by one or more layers of the deep learning network, the input data stream having a plurality of values of a fixed bit width;
• and
• dividing the input data stream into subsets, the number of values in each subset being equal to the number of columns;
• a width detector module having a plurality of bit width registers each associated with a row, the width detector module identifying, for values within the subset, a compressed bit width that accommodates the value with the highest magnitude and storing the bit width in the bit width register associated with the row;
• a compacting module for storing, in the respective column of the memory beginning from a first unoccupied bit, a least significant bits of each value within the subset, the number of bits equal to the bit width, wherein if storing the number of bits requires more bits than those currently left unused in the respective column of the respective row, the remaining bits are written into the respective column of a subsequent row;
• and
• a decompression module for decompressing the compressed data stream to reproduce the input data stream by:
• identifying a first unread bit of each column of the compressed data stream;
• sequentially outputting the reproduced input data by:
• obtaining the bit width of each subset from the respective bit width register;
• retrieving from each column of the first memory, beginning at the first unread bit of the column, the number of bits corresponding to the bit width and outputting the retrieved bits to the least significant bits of an output;
• updating the first unread bit of each column to correspond to the bit location subsequent to the retrieved bits;
• zero or sign extending remaining most significant bits of the output to obtain the reproduced input data value.