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Parallel vectorized algebraic AES in MATLAB for rapid prototyping of encrypted sensor processing algorithms and database analytics
Summary
Summary
The increasing use of networked sensor systems and networked databases has led to an increased interest in incorporating encryption directly into sensor algorithms and database analytics. MATLAB is the dominant tool for rapid prototyping of sensor algorithms and has extensive database analytics capabilities. The advent of high level and high...
Using a power law distribution to describe big data
Summary
Summary
The gap between data production and user ability to access, compute and produce meaningful results calls for tools that address the challenges associated with big data volume, velocity and variety. One of the key hurdles is the inability to methodically remove expected or uninteresting elements from large data sets. This...
Computing on Masked Data to improve the security of big data
Summary
Summary
Organizations that make use of large quantities of information require the ability to store and process data from central locations so that the product can be shared or distributed across a heterogeneous group of users. However, recent events underscore the need for improving the security of data stored in such...
Rapid sequence identification of potential pathogens using techniques from sparse linear algebra
Summary
Summary
The decreasing costs and increasing speed and accuracy of DNA sample collection, preparation, and sequencing has rapidly produced an enormous volume of genetic data. However, fast and accurate analysis of the samples remains a bottleneck. Here we present D4RAGenS, a genetic sequence identification algorithm that exhibits the Big Data handling...
Big Data dimensional analysis
Summary
Summary
The ability to collect and analyze large amounts of data is a growing problem within the scientific community. The growing gap between data and users calls for innovative tools that address the challenges faced by big data volume, velocity and variety. One of the main challenges associated with big data...
Achieving 100,000,000 database inserts per second using Accumulo and D4M
Summary
Summary
The Apache Accumulo database is an open source relaxed consistency database that is widely used for government applications. Accumulo is designed to deliver high performance on unstructured data such as graphs of network data. This paper tests the performance of Accumulo using data from the Graph500 benchmark. The Dynamic Distributed...
Genetic sequence matching using D4M big data approaches
Summary
Summary
Recent technological advances in Next Generation Sequencing tools have led to increasing speeds of DNA sample collection, preparation, and sequencing. One instrument can produce over 600 Gb of genetic sequence data in a single run. This creates new opportunities to efficiently handle the increasing workload. We propose a new method...
LLGrid: supercomputer for sensor processing
Summary
Summary
MIT Lincoln Laboratory is a federally funded research and development center that applies advanced technology to problems of national interest. Research and development activities focus on long-term technology development as well as rapid system prototyping and demonstration. A key part of this mission is to develop and deploy advanced sensor...
Cluster-based 3D reconstruction of aerial video
Summary
Summary
Large-scale 3D scene reconstruction using Structure from Motion (SfM) continues to be very computationally challenging despite much active research in the area. We propose an efficient, scalable processing chain designed for cluster computing and suitable for use on aerial video. The sparse bundle adjustment step, which is iterative and difficult...
Benchmarking parallel eigen decomposition for residuals analysis of very large graphs
Summary
Summary
Graph analysis is used in many domains, from the social sciences to physics and engineering. The computational driver for one important class of graph analysis algorithms is the computation of leading eigenvectors of matrix representations of a graph. This paper explores the computational implications of performing an eigen decomposition of...