Distributed Node Power Estimation for Accurate Job Power Capping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current distributed computer systems face inefficiencies due to inaccurate power estimation, leading to delayed job starts and over-allocation of power, as they rely on thermal dissipation power (TDP) values that do not accurately reflect actual power consumption, causing power management challenges and reduced system performance.
Innovation Solution
The system estimates power performance based on actual measurements, calibration data, and workload types, allowing for precise allocation of power resources to each job, considering variations between nodes and operational frequencies, to optimize power management and reduce wait times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If power capping is applied based on TDP values to adhere to power and energy budgets, then power consumption is controlled, but job performance is negatively impacted due to inaccurate power estimation
Solution Approach 1:
The patent changes the estimation parameter from TDP values to actual measured power consumption values. The system measures the actual power consumed by nodes when running specific workloads and uses these empirical measurements to set accurate power caps, replacing the theoretical TDP-based estimation approach.
Solution Approach 2:
The system implements feedback by measuring actual power consumption during job execution and using these measurements to refine future power allocation decisions. The power management system continuously monitors real power usage and adjusts power caps based on observed consumption patterns, creating a closed-loop control system.
2Device complexity
If TDP values are used to estimate power needed for job startup, then power allocation is simplified, but job start is delayed due to overestimation of necessary power
Solution Approach 1:
The system performs preliminary power measurements during a calibration phase before actual job execution. By pre-measuring the actual power consumption of nodes running representative workloads, the system establishes accurate baseline power requirements that eliminate the need for conservative overestimation, allowing jobs to start immediately with correctly allocated power.
3Ease of operation
If TDP-based power estimation is used, then power allocation is straightforward, but power is over-allocated reducing availability for other jobs
Solution Approach 1:
The system enables nodes to self-report their actual power consumption characteristics through embedded sensors and monitoring infrastructure. Each node measures and reports its own power usage, eliminating the need for conservative system-level estimates and enabling precise, node-specific power allocation that maximizes overall system utilization.
4Device complexity
If TDP is used as the maximum power estimate, then power budgeting is simplified, but the system may attempt to consume more power than allocated by the utility facility
Solution Approach 1:
The patent replaces the theoretical TDP model with empirical electrical measurements. By using actual power consumption data from voltage and current sensors rather than thermal dissipation models, the system achieves accurate real-time power monitoring that ensures utility facility allocations are precisely met without excess consumption.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A non-transitory computer readable storage medium having stored thereon instructions executable by one or more processors to perform operations including: receiving a plurality of input parameters including (i) a workload type, (ii) a list of selected nodes belonging to a distributed computer system, and (iii) a list of frequencies; responsive to receiving the plurality of workload parameters, retrieving calibration data from a calibration database; generating a power estimate based on the plurality of workload parameters and the calibration data; and providing the power estimate to a resource manager is shown. Alternatively, the input parameters may include (i) a workload type, (ii) a list of selected nodes belonging to a distributed computer system, and (iii) an amount of available power, wherein the estimator may provide an estimation of the frequency at which the nodes should operate to utilize as much of the available power without exceeding the available power.