22 citations · 35 across the 5 of their papers we have counts for
5 papers
Decentralized LLM Inference over Edge Networks with Energy Harvesting
Aria Khoshsirat, Giovanni Perin, Michele Rossi
Large language models have significantly transformed multiple fields with their exceptional performance in natural language tasks, but their deployment in resource-constrained envi…
Accurate Calibration of Power Measurements from Internal Power Sensors on NVIDIA Jetson Devices
Neda Shalavi, Aria Khoshsirat, Marco Stellini +2
Power efficiency is a crucial consideration for embedded systems design, particularly in the field of edge computing and IoT devices. This study aims to calibrate the power measure…
Divide and Save: Splitting Workload Among Containers in an Edge Device to Save Energy and Time
Aria Khoshsirat, Giovanni Perin, Michele Rossi
The increasing demand for edge computing is leading to a rise in energy consumption from edge devices, which can have significant environmental and financial implications. To addre…
Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model
Seyyidahmed Lahmer, Aria Khoshsirat, Michele Rossi +1
Recently, there has been a trend of shifting the execution of deep learning inference tasks toward the edge of the network, closer to the user, to reduce latency and preserve data…
A Simple Framework to Quantify Different Types of Uncertainty in Deep Neural Networks for Image Classification
Aria Khoshsirat
Quantifying uncertainty in a model's predictions is important as it enables the safety of an AI system to be increased by acting on the model's output in an informed manner. This i…