Synthesis and optimization of high-level stream programs

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Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

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The dataset supporting 'Fiber pumps for wearable fluidic systems', published in Science in March 2023. In this work, we present a fluidic pump in the form of a flexible and stretchable tube. These tubes - or 'fiber pumps' - can generate significant fluidic ...

Data repository for the following publication: A. Duque-Prata*, H.-Y. Chen*, L. Müller, M. Oppermann, M. Puppin, C. Serpa, C. Bostedt and M. Chergui, “Ultrafast deep-ultraviolet study of photoexcited aqueous Ferrioxalate”, submitted to ChemPhotoCh ...

Dynamically-scheduled elastic circuits generated by High-Level Synthesis (HLS) tools are inherently out-of-order, following the flow of data rather than the evolution of an instruction pointer. Components of the circuit which access memory need to be conne ...

Synthesis from examples enables non-expert users to generate programs by specifying examples of their behavior. A domain-specific form of such synthesis has been recently deployed in a widely used spreadsheet software product. In this paper we contribute t ...

Synthesis and optimization of high-level stream programs

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Validating functional redundancy with mixed generative adversarial networks

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Research data supporting 'Fiber pumps for wearable fluidic systems'

Data for "Ultrafast deep-ultraviolet study of photoexcited aqueous Ferrioxalate"

Optimized Memory Access For Dynamically Scheduled High Level Synthesis

Proactive Synthesis of Recursive Tree-to-String Functions from Examples