In this contributed article, Diederik Verkest, Ph.D. from imec, points out that to make predictions, AI relies on the processing of large amounts of data, a process that takes a lot of energy. Imec develops solutions to drastically reduce that energy consumption. A new chip, in which these calculations are performed directly in the memory by means of analogue technology, is a major breakthrough in this field.
How New Hardware Can Drastically Reduce the Power Consumption of Artificial Intelligence
July 27, 2020 by
Monitoring Power Consumption with the Intelligent Platform Management Interface
April 14, 2016 by
“NWPerf is software that can measure and collect a wide range of performance data about an application or set of applications that run on a cluster. With minimal impact on performance, NWPerf can gather historical information that then can be used in a visualization package. The data collected includes the power consumption using the Intelligent Platform Management Interface (IPMI) for the Intel Xeon processor and the libmicmgmt API for the Intel Xeon Phi coprocessor. Once the data is collected, and using some data extraction mechanisms, it is possible to examine the power used across the cluster, while the application is running.”
Application Performance & Power Consumption on Intel Xeon Phi
April 7, 2016 by
“While new technology will be developed that reduces the power per operation needed, in today’s environments it is important to understand how an application affects power usage. For modern applications that have been optimized to take advantage of both the Intel Xeon CPU and the Intel Xeon Phi coprocessor, the hardware mentioned does include various power states, which can minimize the power consumption when idle.”
