# US 12,602,264 B2 · Data center with energy-aware workload placement > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,602,264 B2 - Document ID: US12602264B2 - Status: Granted - Kind: B2 - Application number: 17/809,284 - Filed: 2022-06-28 - Published: 2023-12-28 - Granted: 2026-04-14 - Earliest claimed: 2022-06-28 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Asser Nasreldin Tantawi; Tamar Eilam; Ramachandra Rao Kolluri; Eun Kyung Lee; Arun Vishwanath; Alaa S. Youssef - Web page: https://patentgrep.com/patent/US12602264B2 ## CPC - G06F 9/5094: {where the allocation takes into account power or heat criteria (power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206)} - G06F 1/3206: Monitoring of events, devices or parameters that trigger a change in power modality - G06F 9/4893: {taking into account power or heat criteria (power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206)} - G06F 11/3058: {Monitoring arrangements for monitoring environmental properties or parameters of the computing system or of the computing system component, e.g. monitoring of power, currents, temperature, humidity, position, vibrations (thermal management in cooling arrangements of a computing system G06F1/206)} - G06F 9/5072: {Grid computing} - G06F 11/3006: {where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems (multiprogramming arrangements G06F9/46; allocation of resources G06F9/50)} - Y02D 10/00: Energy efficient computing, e.g. low power processors, power management or thermal management - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - Y02D: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE ## Abstract A computer-implemented method, a computer system and a computer program product for boosting efficiency through energy-aware workload placement. The method includes obtaining an energy profile for a plurality of computer servers and power consumption data for each computer server in the plurality of computer servers. The method also includes determining an optimal temperature for each computer server in the plurality of computer servers based on the energy profile. The method further includes determining a target processor utilization for each computer server in the plurality of computer servers based on the optimal temperature. In addition, the method includes calculating an efficiency rank for each computer server in the plurality of computer servers based on the target processor utilization and the power consumption data. Lastly, the method includes deploying a workload on a computer server with a highest efficiency rank. ## Claims ### Claim 1 A computer-implemented method for boosting efficiency through energy-aware workload placement, the method comprising: obtaining an energy profile for a plurality of computer servers including power consumption data for each computer server in the plurality of computer servers; determining an optimal temperature for each computer server in the plurality of computer servers based on the energy profile; determining a target processor utilization for each computer server in the plurality of computer servers based on the optimal temperature; calculating an efficiency rank for each computer server in the plurality of computer servers based on the target processor utilization and the power consumption data, wherein the calculated efficiency rank is further based on a combination of a facility efficiency, a server efficiency, and a compute efficiency; and deploying a workload on a computer server with a highest efficiency rank. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the calculating the efficiency rank for each computer server in the plurality of computer servers comprises: identifying a current processor utilization of the computer server; determining the facility efficiency for each computer server in the plurality of computer servers based on the current processor utilization and the target processor utilization; determining the server efficiency for each computer server in the plurality of computer servers based on the power consumption data, wherein the server efficiency measures power consumed by the computer server in the plurality of computer servers with respect to a range of processor utilization for the computer server; determining the compute efficiency for each computer server in the plurality of computer servers based on the current processor utilization and the power consumption data at the current processor utilization; and combining the facility efficiency, the server efficiency, and the compute efficiency for each computer server in the plurality of computer servers. ### Claim 3 (depends on 2) The computer-implemented method of claim 2, wherein the facility efficiency comprises a difference between the target processor utilization and the current processor utilization. ### Claim 4 (depends on 2) The computer-implemented method of claim 2, wherein the compute efficiency comprises a ratio of the current processor utilization to a power consumption at the current processor utilization. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein the determining the target processor utilization for each computer server in the plurality of computer servers uses a machine learning model that predicts an optimal resource utilization from the optimal temperature of a computer server. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, further comprising monitoring the energy profile for the plurality of computer servers and updating the efficiency rank for each computer server based on the energy profile. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein the workload is selected from a list consisting of: a virtual machine (VM) and a container. ### Claim 8 A computer system for boosting efficiency through energy-aware workload placement, the computer system comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage media, and program instructions stored on at least one of the one or more tangible storage media for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising: obtaining an energy profile for a plurality of computer servers including power consumption data for each computer server in the plurality of computer servers; determining an optimal temperature for each computer server in the plurality of computer servers based on the energy profile; determining a target processor utilization for each computer server in the plurality of computer servers based on the optimal temperature; calculating an efficiency rank for each computer server in the plurality of computer servers based on the target processor utilization and the power consumption data, wherein the calculated efficiency rank is further based on a combination of a facility efficiency, a server efficiency, and a compute efficiency; and deploying a workload on a computer server with a highest efficiency rank. ### Claim 9 (depends on 8) The computer system of claim 8, wherein the calculating the efficiency rank for each computer server in the plurality of computer servers comprises: identifying a current processor utilization of the computer server; determining the facility efficiency for each computer server in the plurality of computer servers based on the current processor utilization and the target processor utilization; determining the server efficiency for each computer server in the plurality of computer servers based on the power consumption data, wherein the server efficiency measures power consumed by the computer server in the plurality of computer servers with respect to a range of processor utilization for the computer server; determining the compute efficiency for each computer server in the plurality of computer servers based on the current processor utilization and the power consumption data at the current processor utilization; and combining the facility efficiency, the server efficiency, and the compute efficiency for each computer server in the plurality of computer servers. ### Claim 10 (depends on 9) The computer system of claim 9, wherein the facility efficiency comprises a difference between the target processor utilization and the current processor utilization. ### Claim 11 (depends on 9) The computer system of claim 9, wherein the compute efficiency comprises a ratio of the current processor utilization to a power consumption at the current processor utilization. ### Claim 12 (depends on 8) The computer system of claim 8, wherein the determining the target processor utilization for each computer server in the plurality of computer servers uses a machine learning model that predicts an optimal resource utilization from the optimal temperature of a computer server. ### Claim 13 (depends on 8) The computer system of claim 8, further comprising monitoring the energy profile for the plurality of computer servers and updating the efficiency rank for each computer server based on the energy profile. ### Claim 14 (depends on 8) The computer system of claim 8, wherein the workload is selected from a list consisting of: a virtual machine (VM) and a container. ### Claim 15 A computer program product for boosting efficiency through energy-aware workload placement, the computer program product comprising: a computer-readable storage device having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: obtaining an energy profile for a plurality of computer servers including power consumption data for each computer server in the plurality of computer servers; determining an optimal temperature for each computer server in the plurality of computer servers based on the energy profile; determining a target processor utilization for each computer server in the plurality of computer servers based on the optimal temperature; calculating an efficiency rank for each computer server in the plurality of computer servers based on the target processor utilization and the power consumption data, wherein the calculated efficiency rank is further based on a combination of a facility efficiency, a server efficiency, and a compute efficiency; and deploying a workload on a computer server with a highest efficiency rank. ### Claim 16 (depends on 15) The computer program product of claim 15, wherein the calculating the efficiency rank for each computer server in the plurality of computer servers comprises: identifying a current processor utilization of the computer server; determining the facility efficiency for each computer server in the plurality of computer servers based on the current processor utilization and the target processor utilization; determining the server efficiency for each computer server in the plurality of computer servers based on the power consumption data, wherein the server efficiency measures power consumed by the computer server in the plurality of computer servers with respect to a range of processor utilization for the computer server; determining the compute efficiency for each computer server in the plurality of computer servers based on the current processor utilization and the power consumption data at the current processor utilization; and combining the facility efficiency, the server efficiency, and the compute efficiency for each computer server in the plurality of computer servers. ### Claim 17 (depends on 16) The computer program product of claim 16, wherein the determining the facility efficiency comprises a difference between the target processor utilization and the current processor utilization. ### Claim 18 (depends on 16) The computer program product of claim 16, wherein the compute efficiency comprises a ratio of the current processor utilization to a power consumption at the current processor utilization. ### Claim 19 (depends on 15) The computer program product of claim 15, wherein the determining the target processor utilization for each computer server in the plurality of computer servers uses a machine learning model that predicts an optimal resource utilization from the optimal temperature of a computer server. ### Claim 20 (depends on 15) The computer program product of claim 15, further comprising monitoring the energy profile for the plurality of computer servers and updating the efficiency rank for each computer server based on the energy profile.