18078366. TECHNIQUES FOR DETERMINING A MINIMUM HARDWARE CONFIGURATION USING PERFORMANCE HEADROOM METRICS simplified abstract (Dell Products L.P.)
Contents
TECHNIQUES FOR DETERMINING A MINIMUM HARDWARE CONFIGURATION USING PERFORMANCE HEADROOM METRICS
Organization Name
Inventor(s)
Gajanan S. Natu of Cary NC (US)
Vladimir Shveidel of Pardes-Hana (IL)
Aleksey Kabishcher of Marlborough MA (US)
TECHNIQUES FOR DETERMINING A MINIMUM HARDWARE CONFIGURATION USING PERFORMANCE HEADROOM METRICS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18078366 titled 'TECHNIQUES FOR DETERMINING A MINIMUM HARDWARE CONFIGURATION USING PERFORMANCE HEADROOM METRICS
Simplified Explanation: The patent application describes a method for upgrading the hardware configuration of a data storage system based on a new workload pattern and periodicity interval.
- Receiving a request for a new hardware configuration of a data storage system.
- Modeling the new hardware configuration to run an associated workload with a target scale factor.
- Determining the new hardware configuration based on hardware component utilizations in the current configuration.
- Upgrading the current configuration of the data storage system according to the new hardware configuration.
Key Features and Innovation:
- Method for upgrading hardware configuration based on workload pattern and periodicity interval.
- Target scale factor used to adjust workload in new hardware configuration.
- Optimization of hardware components based on current configuration utilizations.
Potential Applications: The technology can be applied in data centers, cloud computing environments, and storage systems where workload patterns change over time.
Problems Solved:
- Efficiently upgrading hardware configurations in data storage systems.
- Adapting to changing workload patterns without disrupting system performance.
Benefits:
- Improved system performance.
- Cost-effective hardware upgrades.
- Enhanced scalability and flexibility.
Commercial Applications: Optimizing hardware configurations in data centers for improved performance and scalability can benefit cloud service providers, IT companies, and businesses with large data storage needs.
Prior Art: Readers can explore prior research on workload management in data storage systems, hardware configuration optimization, and system performance enhancement.
Frequently Updated Research: Stay informed about the latest advancements in workload management, hardware optimization, and data storage system performance enhancements.
Questions about Hardware Configuration Upgrades: 1. What are the key factors to consider when determining a new hardware configuration for a data storage system? 2. How does the target scale factor impact the workload adjustment in the new hardware configuration?
Original Abstract Submitted
Processing in an embodiment can include: receiving a request for a new hardware configuration of a data storage system, wherein the data storage system has a current configuration and is running a workload W with a workload pattern P having an associated workload periodicity interval, wherein the new hardware configuration is modeled as running an associated workload W with the workload pattern P and the associated workload periodicity interval, wherein the workload W is equal to the workload W multiplied by a target scale factor (TSF); in response to the request, determining the new hardware configuration in accordance with the TSF and a plurality of hardware utilizations of a plurality of hardware components in the current configuration while running the workload W with the workload pattern Phaving the associated workload periodicity interval; and upgrading the current configuration of the data storage system based on the new hardware configuration.
