Essays about: "overhead tasks"
Showing result 1 - 5 of 52 essays containing the words overhead tasks.
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1. Efficiently Solving the Exact Cover Problem in OpenMP
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : The exact cover problem is an NP-complete problem with many widespread use cases such as crew scheduling, railway scheduling, benchmarking as well as having applications in set theory. Existing algorithms can be slow when dealing with large datasets however. READ MORE
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2. IoT as Fog Nodes: An Evaluation on Performance and Scalability
University essay from Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)Abstract : I takt med den exponentiella tillväxten av Internet of Things (IoT) har utmaningen att hantera den enorma mängden genererade data blivit allt större. Denna studie undersöker paradigmen med distribuerade dimdatorer, där kostnadseffektiva IoT-enheter används som dimnoder, som en potentiell lösning på de utmaningarna som det centraliserade molnet står inför. READ MORE
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3. Optimizing Consensus Protocols with Machine Learning Models : A cache-based approach
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Distributed systems offer a reliable and scalable solution for tackling massive and complex tasks that cannot be handled by a single computer. However, standard consensus protocols used in such systems often replicate data without considering the workload, leading to unnecessary retransmissions. READ MORE
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4. Performance Evaluation of Kotlin Multiplatform Mobile and Native iOS Development in Swift
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Today's mobile development resides in the two main operating systems Android and iOS. It is popular to develop mobile applications individually for each respective platform, referred to as native development. To reduce additional costs, cross-platform solutions have emerged that enable shared development for both platforms. READ MORE
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5. Probabilistic Forecasting through Reformer Conditioned Normalizing Flows
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Forecasts are essential for human decision-making in several fields, such as weather forecasts, retail prices, or stock predictions. Recently the Transformer neural network, commonly used for sequence-to-sequence tasks, has shown great potential in achieving state-of-the-art forecasting results when combined with density estimations models such as Autoregressive Flows. READ MORE