17955613. Quality-of-Service Partition Configuration simplified abstract (ATI TECHNOLOGIES ULC)
Contents
- 1 Quality-of-Service Partition Configuration
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 Quality-of-Service Partition Configuration - 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
Quality-of-Service Partition Configuration
Organization Name
Inventor(s)
Tung Chuen Kwong of Richmond Hill (CA)
Akila Subramaniam of Allen TX (US)
Quality-of-Service Partition Configuration - A simplified explanation of the abstract
This abstract first appeared for US patent application 17955613 titled 'Quality-of-Service Partition Configuration
Simplified Explanation
The abstract describes a scheduler for an apparatus that allows applications to specify quality-of-service parameters, such as latency and throughput, for processing workloads using a hardware compute unit. The scheduler configures a partition within the hardware compute unit based on the specified QoS parameters to ensure that processing resources meet the desired quality-of-service.
- The scheduler exposes an API for applications to specify quality-of-service parameters.
- Applications can define QoS parameters like latency and throughput for processing workloads.
- The scheduler configures a partition within the hardware compute unit based on the specified QoS parameters.
- The partition ensures that processing resources meet the specified quality-of-service requirements.
Potential Applications
This technology can be applied in various fields such as cloud computing, edge computing, and real-time data processing where meeting specific quality-of-service requirements is crucial.
Problems Solved
1. Ensuring that workloads are processed with the desired quality-of-service parameters. 2. Optimizing resource allocation within hardware compute units based on specified QoS requirements.
Benefits
1. Improved performance and efficiency in processing workloads. 2. Enhanced user experience by meeting quality-of-service expectations. 3. Flexibility for applications to tailor QoS parameters based on their specific requirements.
Potential Commercial Applications
Optimizing resource allocation in cloud computing environments, improving real-time data processing in edge devices, and enhancing performance in high-demand applications are potential commercial applications of this technology.
Possible Prior Art
Prior art may include existing scheduling algorithms and techniques used in operating systems and cloud computing platforms to manage resource allocation and prioritize tasks based on quality-of-service requirements.
Unanswered Questions
How does the scheduler handle dynamic changes in workload requirements?
The abstract does not specify how the scheduler adapts to changes in quality-of-service parameters during runtime.
What mechanisms are in place to prevent resource contention within the hardware compute unit?
The abstract does not detail how the scheduler manages resource allocation to avoid conflicts and ensure efficient processing of workloads.
Original Abstract Submitted
A scheduler of an apparatus exposes an application programming interface (API) usable to specify quality-of-service (QoS) parameters, e.g., latency, throughput, and so forth. An application, for instance, specifies the QoS parameters for a workload to be processed using a hardware compute unit. The QoS parameters are employed by the scheduler as a basis to configure a partition within a hardware compute unit. The partition is configured such that processing resources that are available via the partition to process the workload comply with the specified quality-of-service.
