US Patent Application 17657912. SYSTEMS AND METHODS FOR SPARSE MATRIX MULTIPLICATION simplified abstract
Contents
SYSTEMS AND METHODS FOR SPARSE MATRIX MULTIPLICATION
Organization Name
Microsoft Technology Licensing, LLC==Inventor(s)==
[[Category:Venmugil Elango of Redmond WA (US)]]
[[Category:Bita Darvish Rouhani of Bellevue WA (US)]]
[[Category:Eric S Chung of Woodinville WA (US)]]
[[Category:Douglas Christopher Burger of Bellevue WA (US)]]
SYSTEMS AND METHODS FOR SPARSE MATRIX MULTIPLICATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17657912 titled 'SYSTEMS AND METHODS FOR SPARSE MATRIX MULTIPLICATION
Simplified Explanation
The patent application describes a method for multiplying sparse matrices efficiently.
- The method involves receiving a first block of elements and dividing it into smaller sub-blocks with a certain level of sparsity.
- A sparsity mask is applied to the first block to ensure that each sub-block has the same level of sparsity.
- A second block of elements is received and divided into sub-blocks with a different level of sparsity.
- A sparsity mask is applied to the second block to ensure that a certain percentage of sub-blocks have no elements and the remaining sub-blocks have all elements.
- Finally, the first and second blocks are multiplied together using matrix multiplication.
Original Abstract Submitted
A method for sparse matrix multiplication comprises receiving a first block having M elements in a first dimension, and parsing the first block of M elements into a first set of B sub-blocks including MB elements in the first dimension. A first sparsity mask having S % sparsity is applied to the first block of elements, such that each of the first set of B sub-blocks has S % sparsity. A second block is received having M elements in a second dimension, and is parsed into a second set of B sub-blocks that include MB elements in the second dimension. A second sparsity mask having S′% sparsity is applied to the second block of elements, such that S′% of the second set of B sub-blocks have 100% sparsity and (100−S′)% of the second set of B sub-blocks have 0% sparsity. The first and second blocks are then matrix multiplied.
