this research examines the effectiveness of XLMRoBERTa, a potent deep learning architecture based on transformers, for POS labeling in Indian languages. Specifically, it concentrates on the UCD dataset(Telugu,Hindi,Ta...
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Sorting is one of the important Data Management Techniques that is quite commonly operated on Data Structures. It has been proved that best, any sorting algorithm can do, in asymptotic versions is φlog2φ, when the i...
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Pulse compression algorithms play an important role in achieving better range resolution (RR) in automobile radar and ultrasonic sensors. the RR is the sensor's capacity to distinguish between two targets position...
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Withthe rapid development of information and communication technology, the demand for communication rate is getting higher and higher. Today's communication system has become more and more difficult to meet the g...
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ISBN:
(数字)9798350355895
ISBN:
(纸本)9798350355901
Withthe rapid development of information and communication technology, the demand for communication rate is getting higher and higher. Today's communication system has become more and more difficult to meet the growing demand for communication rate, high data rate digital demodulator research has increasingly become a hot spot. In order to break through the limitations of the chip clock frequency, parallelization of the demodulator is urgent. this paper conducts research on this and proposes a parallel high data rate demodulator scheme. We focus on parallel matched filtering, parallel timing synchronization, parallel equalization, and parallel carrier synchronization algorithms and implementations, taking into account both resource saving and rate enhancement, and finally complete the simulation to verify its correctness.
Bandit Convex Optimization (BCO) is an imperative analysis framework when dealing with sequential decision-making problems. Considering to balance the computational cost and bounds of regrets, in this paper, we propos...
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Benefitting from the combination of the idea of pipeline with model parallelism and data parallelism, pipeline parallelism improves the efficiency of distributed deep learning systems significantly. However, suffering...
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Deep Neural Networks (DNNs) have become increasingly computationally intensive and have larger parameters, requiring efficient parallelization or distribution using multiple accelerators. Pipeline parallelism has been...
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ISBN:
(纸本)9798400708893
Deep Neural Networks (DNNs) have become increasingly computationally intensive and have larger parameters, requiring efficient parallelization or distribution using multiple accelerators. Pipeline parallelism has been proposed as an effective way to distribute models and improve hardware utilization. However, the problem with pipeline parallelism is the trade-off between speedup and accuracy: synchronous approaches do not provide sufficient speedup, while asynchronous approaches suffer from accuracy degradation due to a different scheme from a single worker. In this paper, we propose AshPipe, a hybrid parallel framework that combines data parallelism and asynchronous pipeline parallelism to achieve efficient speedup for training. the proposed runtime uses the 1F1B schedule and data parallelism, with non-uniform numbers of workers and identical global batch sizes across stages. A Switch parallelism (SP) mechanism is also proposed as an option to mitigate accuracy degradation, which switches over from data parallelism to hybrid parallelism in the course of training. Experimental results show that AshPipe achieves 1.844x the throughput of data parallelism for ViT-H/14 whose parameter size is 632M. Withthe SP mechanism, AshPipe achieved a 30.2% reduction in training time with comparable accuracy compared to data parallelism when training on the CIFAR100 dataset.
the Encoder-Decoder architecture is often used for the seq-to-seq conversion problems in natural language processing. the Encoder is used for feature extraction and the Decoder to generate the sequence. this paper add...
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Malaria is a common and life-threatening disease in our country, with high-risk areas in several villages and hill tracts. Current detection methods are time-consuming and inaccessible. Our system analyzes digital ima...
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the DSP pipeline serial structure restricts the performance of the system, while the FPGA parallelprocessing data high frequency sampling data to meet the design needs. Firstly, this paper introduces the FPGA process...
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