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US 2018/0293758 A1Published application
Low rank matrix compression
AssigneeIntel Corporation
InventorsTomer Bar-On, Jacob Subag, Yaniv Fais, Jeremie Dreyfuss, Gal Novik, Gal Leibovich, Tomer Schwartz, Ehud Cohen, Lev Faivishevsky, Uzi Sarel, Amitai Armon, Yahav Shadmiy
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Abstract
In an example, an apparatus comprises logic, at least partially including hardware logic, to implement a lossy compression algorithm which utilizes a data transform and quantization process to compress data in a convolutional neural network (CNN) layer. Other embodiments are also disclosed and claimed.
Claims20
An apparatus comprising a processor to:
- detect one or more independent rows of a matrix comprising weights of a neural network;
- determine a scalar associated with each of the one or more independent rows of the matrix;
- encode a plurality of the one or more independent rows with the scalar associated with the row to generate encoded weight data;
- apply delta compression to compress the encoded weight data;
- and
- store the encoded weight data in a memory.
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A method, comprising:
- detecting one or more independent rows of a matrix comprising weights of a neural network;
- determining a scalar associated with each of the one or more independent rows of the matrix;
- encoding a plurality of the one or more independent rows with the scalar associated with the row to generate encoded weight data;
- implementing a delta compression algorithm to compress the encoded weight data;
- and
- storing the encoded weight data in a memory.
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An electronic device comprising:
- a computer readable memory;
- and
- a processor communicatively coupled to the computer readable memory to:
- detect one or more independent rows of a matrix comprising weights of a neural network;
- determine a scalar associated with each of the one or more independent rows of the matrix;
- encode a plurality of the one or more independent rows with the scalar associated with the row to generate encoded weight data;
- implement a delta compression algorithm to compress the encoded weight data;
- and
- store the encoded weight data in the computer readable memory.
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Dependencies are inferred from the claim text.