Data inspection for compression/decompression configuration and data type determination
AssigneeNVIDIA Corporation
InventorJeff Pool
Life of this patent
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AssigneeNVIDIA Corporation
InventorJeff Pool
Estimating the term…
Distribution of data in a neural network data set is used to determine an optimal compressor configuration for compressing the neural network data set and/or the underlying data type of the neural network data set. By using a generalizable optimization of examining the data prior to compressor invocation, the example non-limiting technology herein makes it possible to tune a compressor to better target the incoming data. For sparse data compression, this step may involve examining the distribution of data (e.g., in one example, zeros in the data). For other algorithms, it may involve other types of inspection. This changes the fundamental behavior of the compressor itself. By inspecting the distribution of data (e.g., zeros in the data), it also possible to very accurately predict the data width of the underlying data. This is useful because this data type is not always known a priori, and lossy compression algorithms useful for deep learning depend on knowing the true data type to achieve good compression rates.
One or more processing units comprising:
A method comprising:
A data compressor including a processing circuit to:
A non-transitory memory storing instructions that when executed by at least one processor control the at least one processor to perform steps comprising:
A computer system comprising:
A data decompressor comprising:
Dependencies are inferred from the claim text.