相关论文: Terabyte IDE RAID-5 Disk Arrays

Data compaction is a new approach for lossless and lossy compression of read-only array data. The biggest advantage over existing approaches is the possibility to access compressed data without any decompression. This makes data compaction…

In many application domains, the proliferation of sensors and devices is generating vast volumes of data, imposing significant pressure on existing data analysis and data mining techniques. Nevertheless, an increase in data volume does not…

Large-scale Internet of Things (IoT) networks enable intelligent services such as smart cities and autonomous driving, but often face resource constraints. Collecting heterogeneous sensory data, especially in small-scale datasets, is…

Edge computing has become one of the key enablers for ultra-reliable and low-latency communications in the industrial Internet of Things in the fifth generation communication systems, and is also a promising technology in the future sixth…

Large scientific collaborations, often with hundreds or thousands of members, are an excellent opportunity for a case study in best practices implemented while developing open source hardware. Using a publicly available design of timing…

Accessing research data at any time is what FAIR (Findable Accessible Interoperable Reusable) data sharing aims to achieve at scale. Yet, we argue that it is not sustainable to keep accumulating and maintaining all datasets for rapid…

The race for artificial intelligence (AI) dominance often prioritizes scale over efficiency. Hyper-scaling is the common industry approach: larger models, more data, and as many computational resources as possible. Using more resources is a…

The idea of computational storage device (CSD) has come a long way since at least 1990s [1], [2]. By embedding computing resources within storage devices, CSDs could potentially offload computational tasks from CPUs and enable near-data…

Freely and openly shared low-cost electronic applications, known as open electronics, have sparked a new open-source movement, with much un-tapped potential to advance scientific research. Initially designed to appeal to electronic…

High energy physics data is a long term investment and contains the potential for physics results beyond the lifetime of a collaboration. Many existing experiments are concluding their physics programs, and looking at ways to preserve their…

This paper summarizes the idea of Low-Cost Interlinked Subarrays (LISA), which was published in HPCA 2016, and examines the work's significance and future potential. Contemporary systems perform bulk data movement movement inefficiently, by…

Thermoelectric (TE) materials are among very few sustainable yet feasible energy solutions of present time. This huge promise of energy harvesting is contingent on identifying/designing materials having higher efficiency than presently…

Several important and unique experimental high-energy physics programmes at a variety of facilities are coming to an end, including those at HERA, the B-factories and the Tevatron. The wealth of physics data from these experiments is the…

Classical and centralized Artificial Intelligence (AI) methods require moving data from producers (sensors, machines) to energy hungry data centers, raising environmental concerns due to computational and communication resource demands,…

The LHCb collaboration is one of the four major experiments at the Large Hadron Collider at CERN. Many petabytes of data are produced by the detectors and Monte-Carlo simulations. The LHCb Grid interware LHCbDIRAC is used to make data…

Energy storage is needed to enable dispatchable renewable energy supply and thereby full decarbonization of the grid. However, this can only occur with drastic cost reductions compared to current battery technology, with predicted targets…

The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles have gained significant attention as a means to enhance data sharing, collaboration, and reuse across various domains. Here, we explore the potential benefits of…

Real-life industrial use cases for machine learning oftentimes involve heterogeneous and dynamic assets, processes and data, resulting in a need to continuously adapt the learning algorithm accordingly. Industrial transfer learning offers…

The increasing interest in serverless computation and ubiquitous wireless networks has led to numerous connected devices in our surroundings. Among such devices, IoT devices have access to an abundance of raw data, but their inadequate…

As storage systems grow in size, device failures happen more frequently than ever before. Given the commodity nature of hard drives employed, a storage system needs to tolerate a certain number of disk failures while maintaining data…