Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...
Abstract: 3D ultrafast imaging holds great potential across multiple applications, including blood flow imaging, elastography, brain functional ultrasound, cardiac imaging and microvascular flow ...
This project investigates how different multithreaded matrix multiplication strategies affect performance. The objective was to implement parallel matrix multiplication to explore how thread count, ...
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