This work focused on the power estimation of plug load devices, and in particular on Personal Computers. As a result, neural network classification estimated power with less than 5.4% errors. Study showed that internal performance counters properly described the overall system and the main component (CPU and GPU) power. Furthermore, neural networks model demonstrated higher precision on test data than the linear regression model
International audienceThis paper features a novel modeling scheme for power consumption in embedded ...
International audienceThis paper features a novel modeling scheme for power consumption in embedded ...
Efficient power consumption and energy dissipation in embedded devices and modern processors is beco...
In this paper, we present a flexible, simple and accurate power modeling technique that can be used ...
International audienceToday reducing power consumption is a major concern especially when it concern...
In this article, we present a new, simple, accurate, and fast power estimation technique that can be...
International audienceIn this paper, we present a new, simple, accurate and fast power estimation te...
International audiencePower optimization is required all along the design flow but particularly in t...
International audiencePower consumption of servers and applications are of utmost importance as comp...
International audienceWhen high speed and high performance are key features of a specific FPGA-based...
International audienceMuch work has been dedicated to estimating and optimizing workloads in high-pe...
This disclosure describes techniques to predict power consumption of a computing device under design...
The data center industry is responsible for 1.5–2% of the world energy consumption. Energy managemen...
New and complex systems are being implemented using highly advanced Electronic Design Automation (ED...
This paper investigates the energy savings that near-subthreshold processors can obtain in edge AI a...
International audienceThis paper features a novel modeling scheme for power consumption in embedded ...
International audienceThis paper features a novel modeling scheme for power consumption in embedded ...
Efficient power consumption and energy dissipation in embedded devices and modern processors is beco...
In this paper, we present a flexible, simple and accurate power modeling technique that can be used ...
International audienceToday reducing power consumption is a major concern especially when it concern...
In this article, we present a new, simple, accurate, and fast power estimation technique that can be...
International audienceIn this paper, we present a new, simple, accurate and fast power estimation te...
International audiencePower optimization is required all along the design flow but particularly in t...
International audiencePower consumption of servers and applications are of utmost importance as comp...
International audienceWhen high speed and high performance are key features of a specific FPGA-based...
International audienceMuch work has been dedicated to estimating and optimizing workloads in high-pe...
This disclosure describes techniques to predict power consumption of a computing device under design...
The data center industry is responsible for 1.5–2% of the world energy consumption. Energy managemen...
New and complex systems are being implemented using highly advanced Electronic Design Automation (ED...
This paper investigates the energy savings that near-subthreshold processors can obtain in edge AI a...
International audienceThis paper features a novel modeling scheme for power consumption in embedded ...
International audienceThis paper features a novel modeling scheme for power consumption in embedded ...
Efficient power consumption and energy dissipation in embedded devices and modern processors is beco...