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3P-ECLAT: mining partial periodic patterns in columnar temporal databases
Partial periodic pattern (3P) mining is a vital data mining technique that aims to discover all interesting patterns that have exhibited partial...
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An empirical comparison of the performances of single structure columnar in-memory and disk-resident data storage techniques using healthcare big data
Healthcare data in images, texts and other unstructured formats have continued to grow exponentially while generating storage concerns. Even though...
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Partition-based SIMD Processing and its Application to Columnar Database Systems
The Single Instruction Multiple Data (SIMD) paradigm became a core principle for optimizing query processing in columnar database systems. Until now,...
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Temporal-Sequential Learning with Columnar-Structured Spiking Neural Networks
Human can memorize complex temporal sequences, such as music, indicating that the brain has a mechanism for storing time intervals between elements....
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Towards Efficient Discovery of Partial Periodic Patterns in Columnar Temporal Databases
Finding partial periodic patterns in temporal databases is a challenging problem of great importance in many real-world applications. Most previous...
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Memory-Efficient Storing of Timestamps for Spatio-Temporal Data Management in Columnar In-Memory Databases
Vast amounts of spatio-temporal data are continuously accumulated through the wide distribution of location-acquisition technologies. Concerning the...
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Towards Efficient Discovery of Stable Periodic Patterns in Big Columnar Temporal Databases
Extracting stable periodic-frequent patterns in very large temporal databases is a key task in big data analytics. Existing studies have mainly...
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A Method for Data Compression and Personal Information Suppressing in Columnar Databases
Data privacy and security is the need of the hour. The importance elevates further when we submit the data over a network. It is very easy to extract...
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HPCache: memory-efficient OLAP through proportional caching revisited
Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by kee** the most frequently accessed data...
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Towards Efficient Discovery of Periodic-Frequent Patterns in Columnar Temporal Databases
Finding periodic-frequent patterns in temporal databases is a challenging problem of great importance in many real-world applications. Most previous...
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Attractor Properties of Spatiotemporal Memory in Effective Sequence Processing Task
AbstractFor autonomous AI systems, it is important to process spatiotemporal information to encode and memorize it and extract and reuse abstractions...
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BOUNCE: memory-efficient SIMD approach for lightweight integer compression
Integer compression plays an important role in columnar database systems to reduce the main memory footprint as well as to speedup query processing....
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Memory Structures
This chapter covers how Oracle uses memory, both in the individual processes (Process Global Area, or PGA, memory) and shared memory (SGA). We will...
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Accelerating Distributed Knowledge Graph System Based on Non-Volatile Memory
Deploying large scale knowledge graphs on distributed systems has become an industry trend for their high scalability and availability. There are...
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WOBTree: a write-optimized B+-tree for non-volatile memory
The emergence of non-volatile memory (NVM) has introduced new opportunities for performance optimizations in existing storage systems. To better...
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Brain-like Combination of Feedforward and Recurrent Network Components Achieves Prototype Extraction and Robust Pattern Recognition
Associative memory has been a prominent candidate for the computation performed by the massively recurrent neocortical networks. Attractor networks...
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SQL Server In-Memory Technologies
This chapter covers in-memory databases along with some other new technologies and paradigms that radically depart from the traditional disk-based...
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Multi-GPU accelerated cellular automaton model for simulating the solidification structure of continuous casting bloom
The continuous casting bloom is characterized by a large size and long process, leading to tremendous calculation. It takes a long time to simulate...
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CrossIndex: Memory-Friendly and Session-Aware Index for Supporting Crossfilter in Interactive Data Exploration
Crossfilter, a typical application for interactive data exploration (IDE), is widely used in data analysis, BI, and other fields. However, with the...
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An Efficient Bucket Logging for Persistent Memory
Logging is widely used to provide atomicity and durability for transactions in database management systems (DBMSs). For decades, the traditional...