of each MD into subtasks that can be either processed on the MD or offloaded to the server for computation. Then, we formulate the trade-off between energy and delay as a joint optimization problem, which is further represented as a Markov decision process (MDP). To solve this, we desig...
The implementation is described in detail in Fraccaroli et al. (2021). The tricks used in manual approaches to solve problems are mapped into (non-deterministic, and probabilistic) Symbolic Tuning Rules (STRs). These rules identify Tuning Actions (TAs), which have the purpose of editing the ...
This is fast and can be used to find the Pareto front3 across time and power, and solve a user’s optimization goal, e.g. the power mode with the fastest training time for a given power limit, or the lowest power for a given time budget. As is intuitive, PowerTrain has lower ...
DNN is so computation-intensive that user equipment (UE) only to process is not realistic, especially for its limited battery. To solve the problem of long latency and huge energy consumption in mobile device processing, offloading the whole DNN computation to central clouds has been proposed [6...
So far, we have designed and developed nine professional DNN themes. All of our themes come with the BlockBuilder module - a powerful drag and drop page builder that makes building web pages in DNN very easy and fast. There is also the StyleWizard module that helps you to style our DNN...
Motivated by the fact that the data size of some intermediate DNN layers is significantly smaller than that of raw input data, we designed the DNN surgery, which allows partitioned DNN to be processed at both the edge and cloud while limiting the data transmission. The challenge is twofold: ...
This option, designed to identify operator discrepancies, proved unreliable and has been removed. Instead, usetorch.onnx.export(..., report=True, verify=True)option to validate exported models. TheONNXProgramSerializerclass has been removed (#135261) ...
performance of the automatically designed DNN architecture cannot be adequately evaluated. To solve the above problems, this paper proposes a novel three-layer ensemble model, termed consensus particle swarm optimization-assisted trajectory unified and TRUST-TECH ensemble model (CPSOTJUTT-EM). This ...
We present SpanBERT, a pre-training method that is designed to better represent and predict spans of text. Our approach extends BERT by (1) masking contiguous random spans, rather than random tokens, and (2) training the span boundary representations to predict the entire content of the masked...
They are designed to be hard to detect [37], making them particularly suitable for clean-label attacks where the attacker’s objective is to remain stealthy. We selected the SIG attack for this study due to its demonstrated effectiveness in bypassing detection while maintaining a high attack ...