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Erasure codes are being extensively deployed in practical storage systems to prevent data loss with low redundancy. However, these codes require excessive disk I/Os and network traffic for recovering unavailable data. Among all erasure codes, Minimum Storage Regenerating (MSR) codes can achieve...
The growing volume of data produced continuously in the Cloud and at the Edge poses significant challenges for large-scale AI applications to extract and learn useful information from the data in a timely and efficient way. The goal of this article is to explore the use of computational storage...
The rapidly increasing data in recent years requires the datacenter infrastructure to store and process data with extremely high throughput and low latency. Fortunately, persistent memory (PM) and RDMA technologies bring new opportunities towards this goal. Both of them are capable of delivering...
Complex storage stacks providing data compression, indexing, and analytics help leverage the massive amounts of data generated today to derive insights. It is challenging to perform this computation, however, while fully utilizing the underlying storage media. This is because, while storage...
While the computing power of mobile devices has been quickly evolving in recent years, the growth of mobile storage capacity is, however, relatively slower. A common problem shared by budget-phone users is that they frequently run out of storage space. This article conducts a deep inspection of...
In the era of data-intensive computing, large-scale applications, in both scientific and the BigData communities, demonstrate unique I/O requirements leading to a proliferation of different storage devices and software stacks, many of which have conflicting requirements. Further, new hardware...
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