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US 11,232,273 B2Granted
Multiplication-free approximation for neural networks and sparse coding
AssigneeIntel Corporation
InventorsGautham Chinya, Shihao Ji, Arnab Paul
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Abstract
Systems, apparatuses and methods may provide for replacing floating point matrix multiplication operations with an approximation algorithm or computation in applications that involve sparse codes and neural networks. The system may replace floating point matrix multiplication operations in sparse code applications and neural network applications with an approximation computation that applies an equivalent number of addition and/or subtraction operations.
Claims6
A system comprising:
- a scanner;
- a controller to cause the scanner to scan an external image;
- an extractor to extract sparse codes from the scanned external image;
- a comparator to determine a similarity between two unit vectors from the scanned external image based on one or more matrix-vector multiplication operations executed on the two unit vectors;
- and
- an operation substitutor to replace the one or more matrix-vector multiplication operations executed on the two unit vectors with an approximation computation.
3 more elements
Dependencies are inferred from the claim text.