Write-intensive workloads usually cause a large amount of data migration in a drive-managed SMR drive, resulting in performance degradation. Existing research rarely considers about the impact of workload access chara...
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ISBN:
(纸本)9798400710353
Write-intensive workloads usually cause a large amount of data migration in a drive-managed SMR drive, resulting in performance degradation. Existing research rarely considers about the impact of workload access characteristics and data layout on the performance of drive-managed SMR drives. This paper proposes a Zone-weight Aware Performance Acceleration (ZAN) method for drive-managed SMR drives. By utilizing the write access characteristics of workloads, the weights of shingled zones are calculated. And a zone-weight aware data layout strategy and a local read-modify-write operation are designed to reduce the data migration caused by data cleaning. Furthermore, a NVM cache is used in the SMR drive to avoid garbage collection on the media cache. Experimental results show that ZAN can effectively improve the performance of a drive-managed SMR drive.
This paper proposes a multi-class, highly scalable machinelearning algorithm for atrial fibrillation (AF) detection and develops an intelligent diagnostic service plat-form. The AF detection algorithm is divided into...
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The proceedings contain 67 papers. The topics discussed include: optimization of transmission line information management system based on Internet of Things;application of internet of things in smart environmental pro...
ISBN:
(纸本)9781510664913
The proceedings contain 67 papers. The topics discussed include: optimization of transmission line information management system based on Internet of Things;application of internet of things in smart environmental protection in the context of big data;research on risk analysis method of industrial fieldbus based on data analysis;research on tourist volume monitoring system of smart scenic spot;distance education management system for high-tech agricultural talents based on cloud computing;variable screening with binary quantum behavior particle swarm optimization;method for inland water body extraction fused atrous spatial pyramid pooling;personalized recommendation system of modern science and technology resources based on hybrid filtering;research on a new electric power market trading strategy based on power big data;and research on location optimization in third-party logistics management system.
Nowadays, people pay more attention in artificial intelligence(AI) research, and they try to make Al smarter. The machinelearning became a popular subject, especially in object recognition area. Aiming at providing a...
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Gastric cancer (GC) is the fifth most prevalent malignancy in humans and one of the common causes of cancer-related deaths. In 2020, there will be 1.8 million new cases of GC and 770,000 deaths worldwide, which is the...
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With the rapid development of big data technology, the application of machinelearning algorithms is more and more extensive, especially in the field of real data optimization. This study takes random forest, support ...
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Compressed machine (ML) and Deep learning(DL) techniques are the emerging areas in research, the use of compressed ML and DL algorithms is recommended on System on Chip(SoC) platforms as the latencies of ML or DL algo...
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In recent times, recommender systems have acquired significant popularity as a solution to the issue of information overload. These systems offer personalised recommendations to users. The superiority of multi-criteri...
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data Analytics for Athlete Safety in Training (DFAST) is a system designed to improve performance and safety in athlete training. Wearable devices on the athlete send real-time data on movement, accelerations, rotatio...
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In recent years, due to the vigorous development of industrialization, environmental protection measures can not be effectively guaranteed. Increasingly serious environmental problems have gradually become the primary...
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