2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Energy-aware Scheduling of Jobs in Heterogeneous Cluster Systems Using Deep Reinforcement Learning
Amirhossein Esmaili, Massoud Pedram
Energy consumption is one of the most critical concerns in designing computing devices, ranging from portable embedded systems to computer cluster systems. Furthermore, in the past…
Energy-Aware Scheduling of Task Graphs with Imprecise Computations and End-to-End Deadlines
Amirhossein Esmaili, Mahdi Nazemi, Massoud Pedram
Imprecise computations provide an avenue for scheduling algorithms developed for energy-constrained computing devices by trading off output quality with the utilization of system r…
BottleNet: A Deep Learning Architecture for Intelligent Mobile Cloud Computing Services
Amir Erfan Eshratifar, Amirhossein Esmaili, Massoud Pedram
Recent studies have shown the latency and energy consumption of deep neural networks can be significantly improved by splitting the network between the mobile device and cloud. Thi…
Towards Collaborative Intelligence Friendly Architectures for Deep Learning
Amir Erfan Eshratifar, Amirhossein Esmaili, Massoud Pedram
Modern mobile devices are equipped with high-performance hardware resources such as graphics processing units (GPUs), making the end-side intelligent services more feasible. Even r…