18538364. PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS simplified abstract (Intel Corporation)

PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS

Organization Name

Intel Corporation

Inventor(s)

Sundar Nadathur of Cupertino CA (US)

Akhilesh Thyagaturu of Tampa FL (US)

Jonathan L. Kyle of Atlanta GA (US)

Scott M. Baker of Eugene TX (US)

Woojoong Kim of San Jose CA (US)

PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18538364 titled 'PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS

Simplified Explanation

Embodiments for orchestrating execution of workloads on a distributed computing infrastructure are disclosed herein. In one example, environment data is received for compute devices in a distributed computing infrastructure. The environment data is indicative of an operating environment of the respective compute devices and a physical environment of the respective locations of the compute devices. Future operating conditions of the compute devices are predicted based on the environment data, and workloads are orchestrated for execution on the distributed computing infrastructure based on the predicted future operating conditions.

• Predict future operating conditions of compute devices based on environment data
• Orchestrate workloads for execution on distributed computing infrastructure
• Receive environment data for compute devices in the infrastructure
• Environment data includes operating environment and physical environment information
• Improve efficiency and performance of computing infrastructure

Potential Applications

This technology could be applied in various industries such as:

• Cloud computing
• Data centers
• Internet of Things (IoT)
• Edge computing

Problems Solved

• Predicting future operating conditions of compute devices
• Optimizing workload execution on distributed computing infrastructure
• Enhancing overall performance and efficiency of the infrastructure

Benefits

• Improved resource allocation
• Enhanced system reliability
• Increased productivity and cost-effectiveness

Potential Commercial Applications

Optimizing Workload Execution on Distributed Computing Infrastructure: Improving Efficiency and Performance

Possible Prior Art

One possible prior art could be the use of predictive analytics in data centers to optimize resource allocation and workload management.

How does this technology handle unexpected changes in operating conditions of compute devices?

This technology may have mechanisms in place to dynamically adjust workload orchestration based on real-time data and feedback from the compute devices.

What impact does this technology have on energy consumption in a distributed computing infrastructure?

This technology could potentially lead to energy savings by optimizing workload execution and resource allocation, thereby reducing unnecessary energy consumption.

Original Abstract Submitted

Embodiments for orchestrating execution of workloads on a distributed computing infrastructure are disclosed herein. In one example, environment data is received for compute devices in a distributed computing infrastructure. The environment data is indicative of an operating environment of the respective compute devices and a physical environment of the respective locations of the compute devices. Future operating conditions of the compute devices are predicted based on the environment data, and workloads are orchestrated for execution on the distributed computing infrastructure based on the predicted future operating conditions.