Publications
Matched filtering for subgraph detection in dynamic networks
Summary
Summary
Graphs are high-dimensional, non-Euclidean data, whose utility spans a wide variety of disciplines. While their non-Euclidean nature complicates the application of traditional signal processing paradigms, it is desirable to seek an analogous detection framework. In this paper we present a matched filtering method for graph sequences, extending to a dynamic...
Subgraph detection using eigenvector L1 norms
Summary
Summary
When working with network datasets, the theoretical framework of detection theory for Euclidean vector spaces no longer applies. Nevertheless, it is desirable to determine the detectability of small, anomalous graphs embedded into background networks with known statistical properties. Casting the problem of subgraph detection in a signal processing context, this...
Hogs and slackers: using operations balance in a genetic algorithm to optimize sparse algebra computation on distributed architectures
Summary
Summary
We present a framework for optimizing the distributed performance of sparse matrix computations. These computations are optimally parallelized by distributing their operations across processors in a subtly uneven balance. Because the optimal balance point depends on the non-zero patterns in the data, the algorithm, and the underlying hardware architecture, it...
Toward signal processing theory for graphs and non-Euclidean data
Summary
Summary
Graphs are canonical examples of high-dimensional non-Euclidean data sets, and are emerging as a common data structure in many fields. While there are many algorithms to analyze such data, a signal processing theory for evaluating these techniques akin to detection and estimation in the classical Euclidean setting remains to be...
3-d graph processor
Summary
Summary
Graph algorithms are used for numerous database applications such as analysis of financial transactions, social networking patterns, and internet data. While graph algorithms can work well with moderate size databases, processors often have difficulty providing sufficient throughput when the databases are large. This is because the processor architectures are poorly...
High-productivity software development with pMATLAB
Summary
Summary
In this paper, we explore the ease of tackling a communication-intensive parallel computing task - namely, the 2D fast Fourier transform (FFT). We start with a simple serial Matlab code, explore in detail a ID parallel FFT, and illustrate how it can be extended to multidimensional FFTs.
PVTOL: providing productivity, performance, and portability to DoD signal processing applications on multicore processors
Summary
Summary
PVTOL provides an object-oriented C++ API that hides the complexity of multicore architectures within a PGAS programming model, improving programmer productivity. Tasks and conduits enable data flow patterns such as pipelining and round-robining. Hierarchical maps concisely describe how to allocate hierarchical arrays across processor and memory hierarchies and provide a...
pMATLAB parallel MATLAB library
Summary
Summary
MATLAB has emerged as one of the languages most commonly used by scientists and engineers for technical computing, with approximately one million users worldwide. The primary benefits of MATLAB are reduced code development time via high levels of abstractions (e.g. first class multi-dimensional arrays and thousands of built in functions)...
Technical challenges of supporting interactive HPC
Summary
Summary
Users' demand for interactive, on-demand access to a large pool of high performance computing (HPC) resources is increasing. The majority of users at Massachusetts Institute of Technology Lincoln Laboratory (MIT LL) are involved in the interactive development of sensor processing algorithms. This development often requires a large amount of computation...
PMatlab: parallel Matlab library for signal processing applications
Summary
Summary
MATLAB is one of the most commonly used languages for scientific computing with approximately one million users worldwide. At MIT Lincoln Laboratory, MATLAB is used by technical staff to develop sensor processing algorithms. MATLAB'S popularity is based on availability of high-level abstractions leading to reduced code development time. Due to...