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Set queries are fundamental operations in computer networks. This paper addresses the fundamental problem of designing a probabilistic data structure that can quickly process set queries using a small amount of memory. We propose a shifting bloom filter (ShBF) framework for representing and querying sets. We demonstrate the effectiveness of ShBF using three types of popular set queries: membership,...
Given v sets and an incoming item e, multi-set membership query is to report which set contains item e. Multi-set membership query is a fundamental problem in computer systems and applications. All existing data structures cannot achieve small memory usage, fast query speed and high accuracy at the same time. In this paper, we propose a novel probabilistic data structure named Difference Bloom Filter...
A sketch is a probabilistic data structure that is used to record frequencies of items in a multi-set. Sketches have been applied in a variety of fields, such as data stream processing, natural language processing, distributed data sets etc. In this paper, we propose a new sketch, called Slim-Fat (SF) sketch, which has a much smaller memory footprint for query while supporting updates. The key idea...
Modern GPUs open a completely new field to optimize embarrassingly parallel algorithms. Implementing an algorithm on a GPU confronts the programmer with a new set of challenges for program optimization. Some of the most notable ones are isolating the part of the algorithm that can be optimized to run on the GPU; tuning the program for the GPU memory hierarchy whose organization and performance implications...
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