Using the Intel® Energy Checker SDK at Home

For my third blog entry on the Intel® Energy Checker SDK, I will take on a two-part DIY and super fun project. I always wanted to extend the use of the SDK into my home and be able to monitor my personal energy consumption. As an engineer, I live by the motto: “you cannot manage what you cannot measure”. Isn’t the electric bill all about that, one may ask? Sure, it is a good year-to-year and month-to-month trend indicator and it will likely fit the needs of most of us for a while. However, using my bill, I cannot break down my energy consumption per function.

Measuring the energy consumed by a command using the Intel® Energy Checker SDK

In my first blog entry, I showed how simple it was to improve the accuracy of the power draw reported by the Intel® Energy Checker SDK’s stock ESRV simulated device library. I also opened-up for a nice research project consisting of using various system-level data to model more precisely a host system’s power draw. Data such as processor load, memory and I/O usage, P-State or C-State residency are good candidates to explore.

Creating a Simple Device Library for Intel® Energy Checker SDK

For my first blog entry on the Intel® Energy Checker SDK, I will show how to write an ESRV support library which will simulate a power draw slightly more sophisticated than the stock esrv_simulated_device library of the SDK. To give a bit of context, remember that ESRV is the SDK tool in charge of driving a power analyzer and sampling the power and energy readings. This data is then made available to software (SW) using the SDK API. One of the key benefits of processing this way is to completely decouple SW from the burden of measuring power.

Assine o esrv