Maxlinear, Inc.

Michael Ray Ham

Mark Abrian Moran

Pinaki Shankar Chanda

Sasidhar Paruchuri

A method includes obtaining, by a data transform accelerator, a first command and first source data associated with the first command. The method also includes generating, by the data transform accelerator, one or more containers using the first command. Each of the one or more containers may have a container size and may be operable to store compressed source data. The method further includes obtaining a mode of operation for a data compression operation. The method also includes performing the data compression operation to a first portion of the first source data using the mode of operation to obtain the compressed source data. The method further includes storing the compressed source data in a first container of the one or more containers.

Data compression in a data transform accelerator

A method includes determining an address associated with a data transform command in a container data structure which is in the data transform accelerator. The data transform accelerator is in communication with a host computing unit. In response to a determination that the address is in the container data structure, the method includes accessing the data transform command based on the address. The data transform command is in the host computing unit. The method includes obtaining metadata based on information in the data transform command. The metadata is in the data transform accelerator or spread out in the host computing unit memory and in the memory of data transform accelerator. The method includes configuring a data transform pipeline based on the metadata. The metadata can be shared in its entirety or partially by multiple data transform commands grouped together.

Data transform acceleration using metadata stored in accelerator memory

A system for calculating a fingerprint across a data set by identifying a data set to hash, the data set comprising a set of data blocks, identifying data within the data set to skip, generating, by a hash engine, a hash for each data block in the set of data blocks within the data set except for the data within the data set to skip, and compressing the data.

Hashing for deduplication through skipping selected data

A system for calculating a fingerprint across a data set by identifying a data set to hash, the data set comprising a set of data blocks, generating, by a first hash engine, a first hash for each data block in the set of data blocks within the data set, and generating, by a second hash engine, a second hash for each data block in the set of data blocks within the data set.

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San Jose, CA, United States of America

Michael Ray Ham