17967756. CONFIGURING AND DYNAMICALLY RECONFIGURING CHAINS OF ACCELERATORS simplified abstract (Intel Corporation)
Contents
- 1 CONFIGURING AND DYNAMICALLY RECONFIGURING CHAINS OF ACCELERATORS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CONFIGURING AND DYNAMICALLY RECONFIGURING CHAINS OF ACCELERATORS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
CONFIGURING AND DYNAMICALLY RECONFIGURING CHAINS OF ACCELERATORS
Organization Name
Inventor(s)
Saurabh Gayen of Portland OR (US)
Christopher J. Hughes of Santa Clara CA (US)
Utkarsh Y. Kakaiya of Folsom CA (US)
Alexander F. Heinecke of San Jose CA (US)
CONFIGURING AND DYNAMICALLY RECONFIGURING CHAINS OF ACCELERATORS - A simplified explanation of the abstract
This abstract first appeared for US patent application 17967756 titled 'CONFIGURING AND DYNAMICALLY RECONFIGURING CHAINS OF ACCELERATORS
Simplified Explanation
The abstract describes a method for configuring a chain of accelerators to perform a chained accelerator operation, where each accelerator processes data and generates intermediate data for the next accelerator in the chain.
- Receiving a request for a chained accelerator operation
- Configuring a first accelerator to access input data from system memory, process it, and generate first intermediate data
- Configuring a second accelerator to receive the first intermediate data, process it, and generate additional data
Potential Applications
This technology could be applied in high-performance computing, artificial intelligence, data processing, and machine learning applications.
Problems Solved
This technology solves the problem of efficiently processing large amounts of data by chaining accelerators together to perform complex operations without the need to send intermediate data back to system memory.
Benefits
The benefits of this technology include improved processing speed, reduced latency, and increased efficiency in data processing tasks.
Potential Commercial Applications
One potential commercial application of this technology is in data centers where high-speed data processing is required for tasks such as real-time analytics, image processing, and scientific simulations.
Possible Prior Art
Prior art may include similar methods for chaining accelerators together in a processing pipeline to improve data processing speed and efficiency.
Unanswered Questions
How does this method handle errors or interruptions in the data processing chain?
This article does not address how the method handles errors or interruptions that may occur during the data processing chain.
What are the limitations of chaining accelerators together in this manner?
The article does not discuss any potential limitations or drawbacks of chaining accelerators together to perform complex operations.
Original Abstract Submitted
A method of an aspect includes receiving a request for a chained accelerator operation, and configuring a chain of accelerators to perform the chained accelerator operation. This may include configuring a first accelerator to access an input data from a source memory location in system memory, process the input data, and generate first intermediate data. This may also include configuring a second accelerator to receive the first intermediate data, without the first intermediate data having been sent to the system memory, process the first intermediate data, and generate additional data. Other apparatus, methods, systems, and machine-readable medium are disclosed.
