US20140188434A1 - Maintenance prediction of electronic devices using periodic thermal evaluation - Google Patents
Maintenance prediction of electronic devices using periodic thermal evaluation Download PDFInfo
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- US20140188434A1 US20140188434A1 US13/728,174 US201213728174A US2014188434A1 US 20140188434 A1 US20140188434 A1 US 20140188434A1 US 201213728174 A US201213728174 A US 201213728174A US 2014188434 A1 US2014188434 A1 US 2014188434A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/16—Constructional details or arrangements
- G06F1/20—Cooling means
- G06F1/206—Cooling means comprising thermal management
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- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05K—PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS
- H05K7/00—Constructional details common to different types of electric apparatus
- H05K7/20—Modifications to facilitate cooling, ventilating, or heating
- H05K7/20709—Modifications to facilitate cooling, ventilating, or heating for server racks or cabinets; for data centers, e.g. 19-inch computer racks
- H05K7/20836—Thermal management, e.g. server temperature control
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
Definitions
- the claimed subject matter relates generally to thermal systems. More specifically, the claimed subject matter relates to cooling systems for electronic devices.
- servers and other computer devices use integral cooling systems to manage temperature sensitive components.
- One approach to cooling is forced convection. Forced convection cooling involves drawing air inside the device, directing the air to components for cooling.
- the components typically include heat sinks which help move heat away from the components and into the ambient air, which is exhausted out of the device.
- the air drawn into the device contains fibers, dust particles, and other particulates. These particulates accumulate within the devices, causing a condition known as heat sink fouling, which progressively worsens the effectiveness of the cooling system.
- the current approach to address the dust accumulation is to perform regular maintenance to remove the dust.
- air filters may help extend the length of the maintenance period.
- the air filters typically spread the dust over a larger surface area, and merely delay the inevitable maintenance.
- Use of air filters also causes increased flow impedance of a system resulting in system fans to run at higher speed and spend more energy in cooling the system.
- FIG. 1 is a block diagram of an electronic device in accordance with embodiments of the claimed subject matter
- FIG. 2 is a block diagram of a central processing unit (CPU) thermal stack in accordance with embodiments of the claimed subject matter;
- CPU central processing unit
- FIG. 3 is a process flow diagram for a method to schedule thermal system maintenance, in accordance with embodiments.
- FIG. 4 is a block diagram of an example computer system, in accordance with embodiments of the claimed subject matter.
- datacenters schedule maintenance at regular intervals for all servers in a datacenter. Maintenance usually includes cleaning dust and particles from the heat sinks. Regular maintenance helps ensure that the servers stay within power thermal targets.
- the power thermal targets may be budgets for the amount of power dedicated to maintaining environmental temperature. However, this approach is expensive because many systems that are functioning within power thermal targets end up getting serviced.
- FIG. 1 is a block diagram of an electronic device 100 in accordance with embodiments of the claimed subject matter.
- the device 100 may be a computing device, such as a server, desktop computer, laptop, tablet, smart phone, and so on.
- the device 100 includes heat-generating components 102 , heat sinks 104 , fans 106 , a thermal manager 108 , and a performance model 110 .
- the heat-generating components 102 may be a processor, disk drive, high-power semiconductor device, power transistor, optoelectronic device, and so on.
- the heat-generating components 102 include a memory with thermal specifications 114 .
- the temperature specifications 114 identify reliability, functional, and damage limits for the component 102 .
- the reliability limit is a temperature limit to optimize cooling and acoustics.
- the functional limit is a temperature limit to optimize component performance and power management.
- the damage limit is a temperature limit that, when reached, results in the component 102 being shut down to avoid damage.
- the heat sinks 104 are heat exchangers that cool an associated heat-generating component 102 by dissipating the component's heat into the surrounding air.
- the heat sink 104 is connected with a fan 106 , which increases the airflow through the heat sink 104 .
- the fan 106 is operated by the thermal manager 108 , which turns the fan on, off, and sets the fan speed based on current ambient temperature, and the component's operating temperature. It is noted that mobile devices such as phones and tablets use natural-convection cooling, and thus do not include fans 106 .
- Heat sink fouling involves fibers from the air collecting on a surface of the heat sink 104 .
- the fibers accumulate to form a mat that traps finer particulates.
- thermal performance for the heat sink 104 deteriorates. Thermal performance represents the ability of the heat sink 104 to transfer heat away from the associated component 102 .
- the heat sink fouling leads to an increase in fan speed as the thermal manager 108 adjusts speed to maintain the component temperatures within their specified limits. Greater fan speed leads to higher power consumption. Typically, power consumption increases with the mathematical cube of fan speed. The fouling leads to increased flow impedance of the thermal system. This results in reduced airflow and higher component temperatures. Fan speed control algorithms increase fan speed to maintain specified component temperatures. In this way, increased fan speed maintains adequate airflow, even in a state of heat sink fouling.
- Throttling involves decreasing the rate of processing, e.g., CPU processing, to limit the heat generated by the component 102 . Further degradation of the thermal system can lead to the component 102 shutting down to prevent overheating.
- the thermal manager 108 generates a performance model 110 of the thermal system.
- the performance model 110 includes a baseline 114 , and periodic assessments 116 of the thermal system.
- the baseline 114 and assessments 116 are characterizations of the thermal system at a baseline period, when a new device 100 is first installed and powered up, and at scheduled intervals.
- Thermal systems are typically designed with no margin, using a high stress workload condition for the environment to be supported. Accordingly, the baseline 114 and assessments 116 may be generated by running a constant power benchmark. This benchmark provides steady state thermal performance information including, but not limited to, component power consumption, air temperature at component inlet, air temperature at component exhaust, component temperature, and fan speeds.
- the performance model 110 also includes maintenance parameters 118 .
- the maintenance parameters 118 specify conditions for scheduling maintenance.
- the parameters 118 may specify thresholds for power consumption, fan speed, thermal performance, and the like, beyond which maintenance is to be scheduled. These parameters may specify, for example, that maintenance be scheduled if the constant power benchmark shows a 50% power increase in the current assessment 116 over the baseline 114 .
- the thermal manager 108 and performance model 110 are implemented in firmware of the device 100 .
- the thermal manager 108 compares a current assessment 116 to the baseline 114 of the thermal system. If the comparison shows the performance model 110 falls outside the maintenance parameters 118 , maintenance is scheduled for the device 100 . Maintenance may include removing dust from inside the device 100 , around the component 102 and heat sink 104 , and replacing materials of the thermal system.
- the thermal manager 108 estimates the average power increase between the current assessment 116 and the baseline 114 . Additionally, the thermal manager 108 may recommend a maintenance date. The recommended maintenance date is before the component 102 is operating outside the maintenance parameters 118 , and may be based on the average power increase, or on projected time to exceeding a component's thermal specification. During every assessment, the value of parameters such as inlet temperature, component temperature, fan speed, component power, system power, and so on, are stored to create a historical trend. The historical trend is used to project the amount of time that will pass before the component's thermal specification is expected to be exceeded. If this projected time is to end before the next scheduled assessment, an alert is issued to perform maintenance.
- the historical trend is used to project the amount of time that will pass before the component's thermal specification is expected to be exceeded. If this projected time is to end before the next scheduled assessment, an alert is issued to perform maintenance.
- FIG. 2 is a block diagram of a central processing unit (CPU) thermal stack 200 in accordance with an embodiment of the claimed subject matter.
- the CPU thermal stack 200 includes a CPU package 202 and a heat sink 204 , separated by thermal interface materials 1 and 2 , (TIM 1 and TIM 2 ), and an integrated heat spreader (IHS) 206 .
- the CPU package 202 includes the IHS 206 , a CPU 208 on a substrate 210 , plugged into a socket 212 on a motherboard 214 .
- the TIM 1 is a thermal interface material between the CPU and the IHS 206 .
- the TIM 2 is a thermal interface material between the CPU package 202 and the heat sink 204 .
- the TIM 1 and TIM 2 may degrade, thereby degrading the effectiveness of the thermal system. In such a case, removing dust from the component 102 does not provide as much improvement in thermal performance as expected.
- the thermal manager 108 after dust is removed from the component 102 , the thermal manager 108 generates an assessment 116 to determine whether the thermal system is in accord with the thermal specifications 114 . If not, the thermal manager 108 schedules maintenance to replace TIM 2 , and potentially the component itself if TIM 1 has degraded beyond specified parameters 118 .
- FIG. 3 is a process flow diagram for a method 300 to schedule thermal system maintenance, in accordance with embodiments.
- the method begins at block 302 , where the baseline benchmark is run for a specific component 102 .
- the baseline 114 is generated based on the benchmark.
- Block 306 - 316 are repeated at regularly scheduled assessment intervals until the performance model 110 exceeds the maintenance parameters 118 .
- an assessment benchmark is performed.
- the assessment benchmark is used to generate the assessment 116 .
- the value of parameters such as the inlet temperature, component temperature, fan speed, and so on, are stored to create the historical trend.
- the thermal manager 108 generates a historical trend shown by the baseline 114 and the assessments 116 .
- the thermal manager 108 maintains a history of assessment parameter values as a function of assessment dates. Historical data such this is used to evaluate how various parameters are trending, and used in projecting date at which performing maintenance may keep the heat-generating component 102 operating within maintenance parameters 118 .
- the thermal manager determines the average power increase between the baseline 114 and each successive assessment 116 .
- the thermal manager 108 estimates how long until the thermal system is operating outside of the maintenance parameters 118 .
- the historical trend shown by the baseline 114 and the assessments 116 is used to determine the amount of time that passes before the component's thermal specification is expected to be exceeded. If this time is after the next scheduled assessment, at block 316 , a report may be generated that includes, but is not limited to, the average power increase, estimated maintenance date, and projected fan speed increase. If the projected time is before the next scheduled assessment, the method 300 flows to block 318 , where an alert is issued to perform maintenance on the device housing the component.
- the maintenance may be performed.
- the heat sink 104 may be cleaned.
- a new benchmark may be run to generate a new assessment 116 .
- the thermal manager determines whether TIM 2 is to be replaced. If TIM 2 is replaced, a new assessment 116 may be generated to determine whether to replace the component 102 itself due to TIM 1 degradation. TIM 1 is not replaceable.
- the process shown in FIG. 3 may be implemented in any suitable hardware, including logic circuits, one or more processors configured to execute computer-readable instructions, and the like.
- FIG. 4 is a block diagram of an example computer system 400 , in accordance with embodiments.
- the computer system may include, but not be limited to, a server, desktop computer, notebook, tablet, smartphone, and the like.
- the computer system 400 may receive electrical power from a direct current (DC) source (e.g., a battery) or from an alternating current (AC) source (e.g., by connecting to an electrical outlet).
- DC direct current
- AC alternating current
- the computer system 400 includes a central processing unit (CPU) or processor 402 coupled to a bus 404 that provides connectivity to other components of the system 400 .
- CPU central processing unit
- processor 402 coupled to a bus 404 that provides connectivity to other components of the system 400 .
- the processor 402 may include a memory controller (not shown) that is connected to a main memory 404 .
- the main memory 404 may store data and sequences of instructions that are executed by the processor 402 , or any other component included in the system 400 .
- the main memory 404 includes computer-readable media such as, volatile memory and nonvolatile memory.
- the nonvolatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically-programmable ROM (EPROM), electrically-erasable programmable ROM (EEPROM), flash memory, and so on.
- Volatile memory may include random access memory (RAM), such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), DRAM (SLDRAM), direct RAM (RDRAM), direct dynamic RAM (DRDRAM), dynamic RAM (RDRAM).
- RAM random access memory
- SRAM static RAM
- DRAM dynamic RAM
- SDRAM synchronous DRAM
- DDR SDRAM double data rate SDRAM
- ESDRAM enhanced SDRAM
- SLDRAM DRAM
- RDRAM direct RAM
- DRAM dynamic RAM
- RDRAM dynamic RAM
- RDRAM dynamic RAM
- the bus 404 may be connected to a Peripheral Component Interconnect (PCI) bus 408 .
- the PCI bus 408 may provide a data path between the processor 402 and peripheral devices such as, audio device 410 and disk drive 412 . Although not shown, other devices may also be connected to the PCI bus 408 .
- the processor 402 and disk drive 412 are examples of heat-generating devices, each of which is associated with a heat sink 414 , and fan 416 .
- a CPU thermal stack 418 includes the processor 402 and heat sink 414 .
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Abstract
Description
- The claimed subject matter relates generally to thermal systems. More specifically, the claimed subject matter relates to cooling systems for electronic devices.
- Typically, servers and other computer devices use integral cooling systems to manage temperature sensitive components. One approach to cooling is forced convection. Forced convection cooling involves drawing air inside the device, directing the air to components for cooling. The components typically include heat sinks which help move heat away from the components and into the ambient air, which is exhausted out of the device.
- However, the air drawn into the device contains fibers, dust particles, and other particulates. These particulates accumulate within the devices, causing a condition known as heat sink fouling, which progressively worsens the effectiveness of the cooling system. The current approach to address the dust accumulation is to perform regular maintenance to remove the dust. In some cases, air filters may help extend the length of the maintenance period. However, the air filters typically spread the dust over a larger surface area, and merely delay the inevitable maintenance. Use of air filters also causes increased flow impedance of a system resulting in system fans to run at higher speed and spend more energy in cooling the system.
-
FIG. 1 is a block diagram of an electronic device in accordance with embodiments of the claimed subject matter; -
FIG. 2 is a block diagram of a central processing unit (CPU) thermal stack in accordance with embodiments of the claimed subject matter; -
FIG. 3 is a process flow diagram for a method to schedule thermal system maintenance, in accordance with embodiments; and -
FIG. 4 is a block diagram of an example computer system, in accordance with embodiments of the claimed subject matter. - The same numbers are used throughout the disclosure and the figures to reference like components and features. Numbers in the 100 series refer to features originally found in
FIG. 1 ; numbers in the 200 series refer to features originally found inFIG. 2 ; and so on. - In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding. However, it will be apparent to one skilled in the art that embodiments may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring embodiments.
- Reference in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
- Typically, datacenters schedule maintenance at regular intervals for all servers in a datacenter. Maintenance usually includes cleaning dust and particles from the heat sinks. Regular maintenance helps ensure that the servers stay within power thermal targets. The power thermal targets may be budgets for the amount of power dedicated to maintaining environmental temperature. However, this approach is expensive because many systems that are functioning within power thermal targets end up getting serviced.
- Advantageously, when hundreds or thousands of servers are deployed in a datacenter and the datacenter operator, or owner, wants to minimize down-time, it is possible to delay maintenance as long as possible unless power consumption becomes a factor. At that time, cleaning the systems could result in much improved cooling and lower fan power.
-
FIG. 1 is a block diagram of anelectronic device 100 in accordance with embodiments of the claimed subject matter. Thedevice 100 may be a computing device, such as a server, desktop computer, laptop, tablet, smart phone, and so on. Thedevice 100 includes heat-generating components 102,heat sinks 104,fans 106, athermal manager 108, and aperformance model 110. The heat-generating components 102 may be a processor, disk drive, high-power semiconductor device, power transistor, optoelectronic device, and so on. The heat-generatingcomponents 102 include a memory withthermal specifications 114. Thetemperature specifications 114 identify reliability, functional, and damage limits for thecomponent 102. The reliability limit is a temperature limit to optimize cooling and acoustics. The functional limit is a temperature limit to optimize component performance and power management. The damage limit is a temperature limit that, when reached, results in thecomponent 102 being shut down to avoid damage. - The
heat sinks 104 are heat exchangers that cool an associated heat-generating component 102 by dissipating the component's heat into the surrounding air. In some cases, theheat sink 104 is connected with afan 106, which increases the airflow through theheat sink 104. Thefan 106 is operated by thethermal manager 108, which turns the fan on, off, and sets the fan speed based on current ambient temperature, and the component's operating temperature. It is noted that mobile devices such as phones and tablets use natural-convection cooling, and thus do not includefans 106. - Inside the
device 100, various surfaces with narrow air channels or other constrictions can cause heat sink fouling. Heat sink fouling involves fibers from the air collecting on a surface of theheat sink 104. The fibers accumulate to form a mat that traps finer particulates. The more theheat sink 104 becomes blocked, the better the mat becomes at trapping smaller particulates. As a consequence of the fouling, thermal performance for theheat sink 104 deteriorates. Thermal performance represents the ability of theheat sink 104 to transfer heat away from theassociated component 102. - Initially, the heat sink fouling leads to an increase in fan speed as the
thermal manager 108 adjusts speed to maintain the component temperatures within their specified limits. Greater fan speed leads to higher power consumption. Typically, power consumption increases with the mathematical cube of fan speed. The fouling leads to increased flow impedance of the thermal system. This results in reduced airflow and higher component temperatures. Fan speed control algorithms increase fan speed to maintain specified component temperatures. In this way, increased fan speed maintains adequate airflow, even in a state of heat sink fouling. - If fans operate at their maximum speed to maintain component temperature, any additional fouling leads to performance degradation of the
components 102 as a result of throttling. Throttling involves decreasing the rate of processing, e.g., CPU processing, to limit the heat generated by thecomponent 102. Further degradation of the thermal system can lead to thecomponent 102 shutting down to prevent overheating. - In one embodiment, the
thermal manager 108 generates aperformance model 110 of the thermal system. Theperformance model 110 includes abaseline 114, andperiodic assessments 116 of the thermal system. Thebaseline 114 andassessments 116 are characterizations of the thermal system at a baseline period, when anew device 100 is first installed and powered up, and at scheduled intervals. - Thermal systems are typically designed with no margin, using a high stress workload condition for the environment to be supported. Accordingly, the
baseline 114 andassessments 116 may be generated by running a constant power benchmark. This benchmark provides steady state thermal performance information including, but not limited to, component power consumption, air temperature at component inlet, air temperature at component exhaust, component temperature, and fan speeds. - The
performance model 110 also includesmaintenance parameters 118. Themaintenance parameters 118 specify conditions for scheduling maintenance. Theparameters 118 may specify thresholds for power consumption, fan speed, thermal performance, and the like, beyond which maintenance is to be scheduled. These parameters may specify, for example, that maintenance be scheduled if the constant power benchmark shows a 50% power increase in thecurrent assessment 116 over thebaseline 114. In one embodiment, thethermal manager 108 andperformance model 110 are implemented in firmware of thedevice 100. - The
thermal manager 108 compares acurrent assessment 116 to thebaseline 114 of the thermal system. If the comparison shows theperformance model 110 falls outside themaintenance parameters 118, maintenance is scheduled for thedevice 100. Maintenance may include removing dust from inside thedevice 100, around thecomponent 102 andheat sink 104, and replacing materials of the thermal system. - In one embodiment, the
thermal manager 108 estimates the average power increase between thecurrent assessment 116 and thebaseline 114. Additionally, thethermal manager 108 may recommend a maintenance date. The recommended maintenance date is before the component102 is operating outside themaintenance parameters 118, and may be based on the average power increase, or on projected time to exceeding a component's thermal specification. During every assessment, the value of parameters such as inlet temperature, component temperature, fan speed, component power, system power, and so on, are stored to create a historical trend. The historical trend is used to project the amount of time that will pass before the component's thermal specification is expected to be exceeded. If this projected time is to end before the next scheduled assessment, an alert is issued to perform maintenance. -
FIG. 2 is a block diagram of a central processing unit (CPU)thermal stack 200 in accordance with an embodiment of the claimed subject matter. The CPUthermal stack 200 includes aCPU package 202 and aheat sink 204, separated bythermal interface materials 1 and 2, (TIM1 and TIM2), and an integrated heat spreader (IHS) 206. TheCPU package 202 includes the IHS 206, aCPU 208 on a substrate 210, plugged into asocket 212 on amotherboard 214. The TIM1 is a thermal interface material between the CPU and the IHS 206. The TIM2 is a thermal interface material between theCPU package 202 and theheat sink 204. - Over time, the TIM1 and TIM2 may degrade, thereby degrading the effectiveness of the thermal system. In such a case, removing dust from the
component 102 does not provide as much improvement in thermal performance as expected. In one embodiment, after dust is removed from thecomponent 102, thethermal manager 108 generates anassessment 116 to determine whether the thermal system is in accord with thethermal specifications 114. If not, thethermal manager 108 schedules maintenance to replace TIM2, and potentially the component itself if TIM1 has degraded beyond specifiedparameters 118. -
FIG. 3 is a process flow diagram for amethod 300 to schedule thermal system maintenance, in accordance with embodiments. The method begins atblock 302, where the baseline benchmark is run for aspecific component 102. Atblock 304, thebaseline 114 is generated based on the benchmark. - Block 306-316 are repeated at regularly scheduled assessment intervals until the
performance model 110 exceeds themaintenance parameters 118. Atblock 308, an assessment benchmark is performed. The assessment benchmark is used to generate theassessment 116. The value of parameters such as the inlet temperature, component temperature, fan speed, and so on, are stored to create the historical trend. - At
block 310, thethermal manager 108 generates a historical trend shown by thebaseline 114 and theassessments 116. Thethermal manager 108 maintains a history of assessment parameter values as a function of assessment dates. Historical data such this is used to evaluate how various parameters are trending, and used in projecting date at which performing maintenance may keep the heat-generatingcomponent 102 operating withinmaintenance parameters 118. - Based on the historical trend, at
block 312, the thermal manager determines the average power increase between thebaseline 114 and eachsuccessive assessment 116. Atblock 314, thethermal manager 108 estimates how long until the thermal system is operating outside of themaintenance parameters 118. The historical trend shown by thebaseline 114 and theassessments 116 is used to determine the amount of time that passes before the component's thermal specification is expected to be exceeded. If this time is after the next scheduled assessment, atblock 316, a report may be generated that includes, but is not limited to, the average power increase, estimated maintenance date, and projected fan speed increase. If the projected time is before the next scheduled assessment, themethod 300 flows to block 318, where an alert is issued to perform maintenance on the device housing the component. - At
block 320, the maintenance may be performed. For example, theheat sink 104 may be cleaned. - At
block 322, a new benchmark may be run to generate anew assessment 116. Atblock 324, the thermal manager determines whether TIM2 is to be replaced. If TIM2 is replaced, anew assessment 116 may be generated to determine whether to replace thecomponent 102 itself due to TIM1 degradation. TIM1 is not replaceable. - The process shown in
FIG. 3 may be implemented in any suitable hardware, including logic circuits, one or more processors configured to execute computer-readable instructions, and the like. -
FIG. 4 is a block diagram of anexample computer system 400, in accordance with embodiments. The computer system may include, but not be limited to, a server, desktop computer, notebook, tablet, smartphone, and the like. Although not shown, thecomputer system 400 may receive electrical power from a direct current (DC) source (e.g., a battery) or from an alternating current (AC) source (e.g., by connecting to an electrical outlet). Thecomputer system 400 includes a central processing unit (CPU) orprocessor 402 coupled to abus 404 that provides connectivity to other components of thesystem 400. - The
processor 402 may include a memory controller (not shown) that is connected to amain memory 404. Themain memory 404 may store data and sequences of instructions that are executed by theprocessor 402, or any other component included in thesystem 400. In one embodiment, themain memory 404 includes computer-readable media such as, volatile memory and nonvolatile memory. The nonvolatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically-programmable ROM (EPROM), electrically-erasable programmable ROM (EEPROM), flash memory, and so on. - Volatile memory may include random access memory (RAM), such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), DRAM (SLDRAM), direct RAM (RDRAM), direct dynamic RAM (DRDRAM), dynamic RAM (RDRAM).
- The
bus 404 may be connected to a Peripheral Component Interconnect (PCI)bus 408. ThePCI bus 408 may provide a data path between theprocessor 402 and peripheral devices such as,audio device 410 anddisk drive 412. Although not shown, other devices may also be connected to thePCI bus 408. - The
processor 402 anddisk drive 412 are examples of heat-generating devices, each of which is associated with aheat sink 414, andfan 416. A CPUthermal stack 418 includes theprocessor 402 andheat sink 414. - It is to be understood that specifics in the aforementioned examples may be used anywhere in one or more embodiments. For instance, features of the computing device described above may alternatively be implemented with respect to either of the methods or the computer-readable medium described herein. Furthermore, although the Figures herein describe embodiments, embodiments of the claimed subject matter are not limited to those diagrams or corresponding descriptions. For example, flow need not move through each illustrated box of
FIG. 4 in the same specific order as illustrated herein. - Embodiments are not restricted to the particular details listed herein. Indeed, those skilled in the art having the benefit of this disclosure will appreciate that many other variations from the foregoing description and drawings may be made. Accordingly, it is the following claims, including any amendments thereto, that define the scope.
Claims (30)
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PCT/US2013/076549 WO2014105634A1 (en) | 2012-12-27 | 2013-12-19 | Maintenance prediction of electronic devices using periodic thermal evaluation |
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WO2014105634A1 (en) | 2014-07-03 |
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CN104335133B (en) | 2019-08-13 |
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