Deep learning has transformed medical imaging by significantly improving accuracy and efficiency in image processing tasks such as disease detection, segmentation, and classification. this paper explores the role of c...
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this research paper aims to enhance the performance of Number theoretic Transform (NTT) operations in cryptographic applications by leveraging the flexibility and parallelprocessing capabilities of Field Programmable...
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the study of bioinformatics-based evolutionary computation has long been of significant interest within the scientific community. Beetle antennae search algorithm is widely used because of its lightweight, however, it...
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In this paper, we propose a parallel implementation of the number-theoretic transform (NTT) on GPU clusters. the butterfly operation of the NTT can be performed using modular addition, subtraction, and multiplica...
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Reinforcement Learning from Human Feedback (RLHF) technology provides a method for agents to learn human preferences and perform actions that satisfy human desires. this technology was originally used to complete robo...
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the breadth-first search (BFS) algorithm is a fundamental algorithm in graph theory, and it’s parallelization can significantly improve performance. therefore, there have been numerous efforts to leverage the powerfu...
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Currently, the landscape of computer hardware architecture presents the characteristics of heterogeneity and diversity, prompting widespread attention to cross-platform portable parallel programming techniques. Most e...
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Large language models have garnered significant attention and are widely utilized across different fields due to their impressive performance. However, centralized training of these models can pose privacy risks like ...
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