In this work, we introduce a power-consumption model for heterogeneous multicore architectures that captures the variability of energy consumption based on processing workload type, in addition to the classical variables considered in the literature, like type and frequency of the CPU. We motivate the approach presenting experimental results gathered on a Odroid-XU3 board equipped with an Arm big.LITTLE CPU, showing that power consumption has a non-negligible dependency on the workload type. We also present a model to define the execution time of the tasks, which depends on both the workload, and the CPU frequency and architecture. We present our modifications to the open-source RTSIM real-time scheduling simulator to extend its CPU power c...
Nowadays, reducing energy consumption and improving the energy efficiency of computing systems becom...
International audienceThe search for optimal mapping of application (tasks) onto processor architect...
International audienceWhile distributed computing infrastructures can provide infrastructure-level t...
In this work, we introduce a power-consumption model for heterogeneous multicore architectures that ...
In this paper, we present PARTSim, an open-source power/thermal-aware simulator for embedded real-ti...
International audienceSophisticated applications turn out to be executed upon more than one CPU for ...
this is the author’s version of a work that was accepted for publication in Future Generation Comput...
Abstract—As application complexity increases, modern embedded systems have adopted heterogeneous pro...
ARM big.LITTLE architectures are spreading more and more in the mobile world thanks to their power-s...
This paper presents the modeling of embedded systems with SimBed, an execution-driven simulation tes...
This paper presents a power-aware scheduling algorithm based on efficient distribution of the comput...
Power- and energy-efficiency continues to be a primary concern in the design and management of compu...
In this paper, we investigate the impact of scheduler overhead on energy-efficient, real-time schedu...
Modern processors are becoming increasingly more complex and utilise higher numbers of Heterogeneous...
Nowadays, reducing energy consumption and improving the energy efficiency of computing systems becom...
International audienceThe search for optimal mapping of application (tasks) onto processor architect...
International audienceWhile distributed computing infrastructures can provide infrastructure-level t...
In this work, we introduce a power-consumption model for heterogeneous multicore architectures that ...
In this paper, we present PARTSim, an open-source power/thermal-aware simulator for embedded real-ti...
International audienceSophisticated applications turn out to be executed upon more than one CPU for ...
this is the author’s version of a work that was accepted for publication in Future Generation Comput...
Abstract—As application complexity increases, modern embedded systems have adopted heterogeneous pro...
ARM big.LITTLE architectures are spreading more and more in the mobile world thanks to their power-s...
This paper presents the modeling of embedded systems with SimBed, an execution-driven simulation tes...
This paper presents a power-aware scheduling algorithm based on efficient distribution of the comput...
Power- and energy-efficiency continues to be a primary concern in the design and management of compu...
In this paper, we investigate the impact of scheduler overhead on energy-efficient, real-time schedu...
Modern processors are becoming increasingly more complex and utilise higher numbers of Heterogeneous...
Nowadays, reducing energy consumption and improving the energy efficiency of computing systems becom...
International audienceThe search for optimal mapping of application (tasks) onto processor architect...
International audienceWhile distributed computing infrastructures can provide infrastructure-level t...