Publications
Dynamic Distributed Dimensional Data Model (D4M) database and computation system
Summary
Summary
A crucial element of large web companies is their ability to collect and analyze massive amounts of data. Tuple store databases are a key enabling technology employed by many of these companies (e.g., Google Big Table and Amazon Dynamo). Tuple stores are highly scalable and run on commodity clusters, but...
Fundamental Questions in the Analysis of Large Graphs
Summary
Summary
Graphs are a general approach for representing information that spans the widest possible range of computing applications. They are particularly important to computational biology, web search, and knowledge discovery. As the sizes of graphs increase, the need to apply advanced mathematical and computational techniques to solve these problems is growing...
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.
Radar Signal Processing: An Example of High Performance Embedded Computing
Summary
Summary
This chapter focuses on the computational complexity of the front-end of the surface moving-target indication (SMTI) radar application. SMTI radars can require over one trillion operations per second of computation for wideband systems. The adaptive beamforming performed in SMTI radars is one of the major computational complexity drivers. The goal...
pMapper: automatic mapping of parallel Matlab programs
Summary
Summary
Algorithm implementation efficiency is key to delivering high-performance computing capabilities to demanding, high throughput DoD signal and image processing applications and simulations. Significant progress has been made in compiler optimization of serial programs, but many applications require parallel processing, which brings with it the difficult task of determining efficient mappings...
Automatic parallelization with pMapper
Summary
Summary
Algorithm implementation efficiency is key to delivering high-performance computing capabilities to demanding, high throughput signal and image processing applications and simulations. Significant progress has been made in optimization of serial programs, but many applications require parallel processing, which brings with it the difficult task of determining efficient mappings of algorithms...
Discrete optimization using decision-directed learning for distributed networked computing
Summary
Summary
Decision-directed learning (DDL) is an iterative discrete approach to finding a feasible solution for large-scale combinatorial optimization problems. DDL is capable of efficiently formulating a solution to network scheduling problems that involve load limiting device utilization, selecting parallel configurations for software applications and host hardware using a minimum set of...