REORDERING OF SPARSE DATA TO INDUCE SPATIAL LOCALITY FOR N-DIMENSIONAL SPARSE CONVOLUTIONAL NEURAL NETWORK PROCESSING

• Main Authors: Subramoney, Sreenivas, Omer, Om, Thyagharajan, Anirud, Laddha, Prashant
• Format: Patent
• Language: English; French; German
• Published: 03.11.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; PHYSICS

Exemplary embodiments maintain spatial locality of the data being processed by a sparse CNN. The spatial locality is maintained by reordering the data to preserve spatial locality. The reordering may be performed on data elements and on data for groups of co-located data elements referred to herein as "chunks". Thus, the data may be reordered into chunks, where each chunk contains data for spatially co-located data elements, and in addition, chunks may be organized so that spatially located chunks are together. The use of chunks helps to reduce the need to re-fetch data during processing. Chunk sizes may be chosen based on the memory constraints of the processing logic (e.g., cache sizes).