- #INTEL DYNAMIC PLATFORM AND THERMAL FRAMEWORK DRIVER LENOVO HOW TO#
- #INTEL DYNAMIC PLATFORM AND THERMAL FRAMEWORK DRIVER LENOVO SKIN#
The problem with that approach was that when the device was placed in a situation where cooling was better, such as held vertically in the air or held in a dock with a circulation fan, DPTF wouldn’t change the temperature sensor correlations to skin temperature.
#INTEL DYNAMIC PLATFORM AND THERMAL FRAMEWORK DRIVER LENOVO HOW TO#
With previous iterations of DPTF, this worst-case style setup was what was used to determine how to correlate temperature sensors with skin temperatures. For example, when a tablet is placed flat on a table with the display up, the back of the tablet is unable to rely on convection and ambient air flow to cool the back cover. One of the key examples cited is device orientation, as how a device is placed has a significant impact on its ability to cool itself. Instead of a fixed correlation, the system is now adaptive depending upon a number of factors. However in the case of DPTF 8.1, this system has changed. Similarly, if an on-die chip sensor reads a specific value that is close to the maximum junction temperature, the system will react by throttling appropriately.
And once certain temperature sensors read out certain values, the system assumes that the skin temperature has reached a maximum value, which means it’s necessary to begin throttling the system. As these devices are unable to directly read skin temperatures, the system must instead infer what Tskin should be. If you think this sounds a lot like ARM’s Intelligent Power Allocation in some ways, you’d be right.įor the most part, previous iterations of DPTF have been pretty standard in the sense that they rely on a fixed correlation between temperature sensors and critical values like Tskin max and Tjunction max of all chips on the board.
For those that are probably unaware of what Intel’s DPTF is, it’s effectively Intel’s solution to managing throttling in a smart manner according to the TDP limits of the device based upon thermal sensors and power monitoring for x86 tablets, 2-in-1s, and PCs in general. For the end user then, there’s a clear benefit to both effective turbo and thermal management, as any kind of race to sleep workload sees benefit from turbo clocks, while long-running high-load workloads benefit significantly from smart thermal management.Īlthough Intel’s Dynamic Platform and Thermal Framework (DPTF) 8.1.x has been out for months now, these features haven’t really received much attention so far. This has been evidenced in recent years by the ever-increasing dynamic power ranges for mobile CPUs, which has seen idle power consumption drop while maximum load power consumption has risen.īy increasing the dynamic range of these CPUs, it has allowed manufacturers to further optimize their devices for workloads that require high CPU performance for only short periods of time, a surprisingly common workload.
This means that while performance per watt will increase from generation to generation thanks to manufacturing and architectural improvements, finding ways to allow CPUs to use more power is also part of the equation in order to get the best possible performance out of a passively cooled device. We can use CMOS scaling to try and reduce the amount of power consumption, but in order to keep up with increasing performance demands it’s important to also scale performance as well. In mobile, thermal throttling is effectively a fact of life as modern, thin tablets and smartphones leave little room for implementing high-performance fans.
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