Storage edge controller with a metadata computational engine

Patent metadata

Field	Value
Publication number	US-2020042240-A1
Application number	US-201916264473-A
Country	US
Kind code	A1
Filing date	Jan 31, 2019
Priority date	Jul 31, 2018
Publication date	Feb 6, 2020
Grant date	—

Abstract

Embodiments described herein provide improved methods and systems for generating metadata for media objects at a computational engine (such as an artificial intelligence engine) within the storage edge controller, and for storing and using such metadata, in data processing systems.

First claim

What is claimed is:

1 . A storage device controller for managing storage and retrieval of data at one or more storage devices, the storage device controller comprising:
a host interface configured to communicate with one or more hosts; a memory interface, configured to communicate locally with a non-volatile memory of the one or more storage devices; a first processor configured to manage local storage or retrieval of objects at the non-volatile memory; and
a computational engine configured to:
obtain, from a volatile memory, a first computational model and a set of parameters for implementing the first computational model, and
selectively compute, using the first computational model, metadata that defines content characteristics of the objects that are retrieved from the non-volatile memory or that are received from the one or more hosts for storage in the non-volatile memory.

2 . The storage device controller of claim 1 , wherein the volatile memory is a dynamic random-access memory coupled to the storage device controller.

3 . The storage device controller of claim 1 , wherein the volatile memory is a host memory buffer allocated by a host system to the storage device controller, and wherein the host memory buffer is accessible by the storage device controller over a computer network connection, or a bus connection.

4 . The storage device controller of claim 1 , wherein the computational engine comprises:
a second processor that is separate from the first processor and is configured to perform computational tasks relating to metadata generation including implementing the first computational model, and wherein the first processor is configured to:
send a computational task relating to metadata generation to the second processor at the computational engine without taking up resource of the first processor for an ongoing operation being performed by the storage device controller.

5 . The storage device controller of claim 4 , wherein the computational engine further comprises:
a volatile memory coupled to the second processor, wherein the volatile memory is a static random-access memory configured to cache at least a portion of the objects during computation of the metadata that defines content characteristics of the cached portion of objects.

6 . The storage device controller of claim 1 , wherein the first processor is further configured to:
receive, via the host interface, the objects from the one or more hosts, wherein the objects are to be stored at the non-volatile memory; temporarily store the received objects at a volatile memory disposed within the storage device controller for metadata computation; after computation of the metadata that defines content characteristics of the objects is completed:
send, via the memory interface, the received objects from the volatile memory to the non-volatile memory for storage; and
perform at least one of: sending, via the host interface, the metadata to the host system, and sending, via the memory interface, the metadata to the non-volatile memory for storage.

7 . The storage device controller of claim 1 , wherein the first processor is further configured to:
receive, via the host interface, a command from a host system of the one or more hosts to retrieve the objects from the non-volatile memory; in response to the command, retrieve, via the memory interface, the objects from the volatile memory disposed within the storage controller for metadata computation; and after computation of metadata defining content characteristics of the objects is completed, send, via the memory interface, the metadata and the objects to the non-volatile memory for storage.

8 . The storage device controller of claim 1 , wherein the first processor is further configured to:
receive, via the host interface and from the one or more hosts, a request for metadata while the computational engine is computing the metadata; and respond to the request for metadata asynchronously by:
waiting until the requested metadata is computed at the computational engine; and
sending, via the host interface, the requested metadata to the host system while new metadata, different from the requested metadata, is being computed at the computational engine.

9 . The storage device controller of claim 7 , wherein the first processor is further configured to:
in response to the command, determine whether the command from the host system requires an update of the first computational model; in response to determining that the command from the host system does not require an update of the computational model, instruct the computational engine to implement an existing computational model; in response to determining that the command from the host system requires the first computational model to be updated to a second computational model different from the first computational model:
retrieve a set of updated parameters for the second computational model from the volatile memory disposed within the storage controller, or, via the host interface, from a host buffer memory disposed within the host system, and
send the set of updated parameters to the computational engine to implement the second computational model.

10 . The storage device controller of claim 1 , wherein the computational engine is further configured to automatically generate metadata that defines content characteristics of the objects by performing any of identification of persons of interest or other objects; customized insertion of advertisements into streamed videos; cloud-based analytics of data from autonomous vehicles; analytics of call and response quality in a ChatBot Voice calls database, text documents and text messages database analysis; mood detection; scene identification within a video file or voice call; identification of persons or objects in surveillance footage; identification of types of actions occurring in surveillance footage; identification of voices or types of sounds in recordings; classification of phrases and responses used during conversations; and analysis of automotive sensor data and driving response.

11 . A method for managing storage and retrieval of data at one or more storage devices, the method comprising:
communicating, via a host interface of a storage device controller, with one or more hosts; communicating, via a memory interface of the storage device controller, locally with a non-volatile memory of the one or more storage devices; managing, via a first processor of the storage device controller, local storage or retrieval of objects at the non-volatile memory; obtaining, from a volatile memory, a first computational model and a set of parameters to implement the first computational model; and selectively computing, via a computational engine using the computational model, metadata that defines content characteristics of the objects that are retrieved from the non-volatile memory or that are received from the one or more hosts for storage in the non-volatile memory.

12 . The method of claim 11 , further comprising:
storing parameters of the first computational model for the computational engine at the volatile memory,
wherein the volatile memory is a dynamic random-access memory coupled to the storage device controller.

13 . The method of claim 11 , further comprising:
storing parameters of the computational model for the computational engine at the volatile memory, wherein the volatile memory is a host memory buffer allocated by a host system to the storage device controller, and wherein the host memory buffer is accessible by the storage device controller over a computer network connect

Assignees

• Marvell Int Ltd

Inventors

• Therene Christophe
• Varnica Nedeljko
• Kudryavtsev Konstantin
• Shrivastava Manish
• Oberg Mats
• Mizrahi Noam
• Jiang Leo

Classifications

• G06F3/0638

  Organizing or formatting or addressing of data · CPC title

• G06F16/387

  using geographical or spatial information, e.g. location · CPC title

• G06F16/907 Primary

  Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually · CPC title

• G06F16/383

  using metadata automatically derived from the content · CPC title

• G06F3/068

  Hybrid storage device · CPC title