17935709. DYNAMIC HETEROGENEOUS TASK PROCESSING simplified abstract (GOOGLE LLC)

From WikiPatents
Jump to navigation Jump to search

DYNAMIC HETEROGENEOUS TASK PROCESSING

Organization Name

GOOGLE LLC

Inventor(s)

Jamie Menjay Lin of San Diego CA (US)

Chuo-Ling Chang of Mountain View CA (US)

DYNAMIC HETEROGENEOUS TASK PROCESSING - A simplified explanation of the abstract

This abstract first appeared for US patent application 17935709 titled 'DYNAMIC HETEROGENEOUS TASK PROCESSING

Simplified Explanation

The patent application describes a method for processing a stream of data by determining features associated with a block of data and selecting a task based on these features to process the data. If a second task is selected, the output is shifted in time to align with the predicted output of the first task processing the next block of data.

  • The method involves processing a stream of data in a sequence of tasks.
  • Features associated with a block of data are determined to select a task for processing.
  • The output of the second task is shifted in time to align with the predicted output of the first task processing the next block of data.

Potential Applications

This technology could be applied in various industries such as telecommunications, data analysis, and signal processing.

Problems Solved

This technology helps in optimizing the processing of data streams by selecting tasks based on features and aligning outputs for efficient data processing.

Benefits

The method improves data processing efficiency, reduces processing time, and enhances overall system performance.

Potential Commercial Applications

"Stream Data Processing Method for Efficient Task Selection and Output Alignment"

Possible Prior Art

There may be prior art related to stream data processing methods in various fields such as telecommunications, data analytics, and signal processing.

Unanswered Questions

How does this method handle real-time data processing?

The patent application does not specify how real-time data processing is managed using this method.

What are the potential limitations of this technology in handling large volumes of data?

The patent application does not address the potential limitations of this technology when processing large volumes of data.


Original Abstract Submitted

A method including processing a stream of data in a sequence of tasks. The processing including receiving a first block of data of the stream of data, determining features associated with the first block of data, selecting, based on the features, one of a first a task to process the first block of data or a second task to process the first block of data and if the second task is selected, shift an output of the second task in time to align the output of the second task with a predicted output of the first task processing a second block of data of the stream of data.