FPGA Acceleration of Mean Variance Framework for Optimal Asset Allocation

Asset classes respond differently to shifts in financial markets, thus an investor can minimize the risk of loss and maximize return of his portfolio by diversification of assets. Increasing the number of diversified assets in a financial portfolio significantly improves the optimal allocation of different assets giving better investment opportunities. However, a large number of assets require a significant amount of computation that only high performance computing can currently provide. Because of the highly parallel nature of Markowitzpsila mean variance framework (the most popular approximation approach for optimal asset allocation) an FPGA implementation of the framework can also provide the performance necessary to compute the optimal asset allocation with a large number of assets. In this work, we propose an FPGA implementation of Markowitzpsila mean variance framework and show it has a potential performance ratio of 221 times over a software implementation

GUSTO: An automatic generation and optimization tool for matrix inversion architectures

Matrix inversion is a common function found in many algorithms used in wireless communication systems. As FPGAs become an increasingly attractive platform for wireless communication, it is important to understand the trade-offs in designing a matrix inversion core on an FPGA. This article describes a matrix inversion core generator tool, GUSTO, that we developed to ease the design space exploration across different matrix inversion architectures. GUSTO is the first tool of its kind to provide automatic generation of a variety of general-purpose matrix inversion architectures with different parameterization options. GUSTO also provides an optimized applicationspecific architecture with an average of 59% area decrease and 3X throughput increase over its general-purpose architecture. The optimized architectures generated by GUSTO provide comparable results to published matrix inversion architecture implementations, but offer the advantage of providing the designer the ability to study the trade-offs between architectures with different design parameters

Distributed Multi-robot Coordination For Area Exploration and Mapping

Steady advances in technology, design tools and mobile communication networks have extensively expanded the application domain of robotics over the past decade. In recent days, small, portable and mobile robot platforms have numerous applications like search and rescue, reconnaissance, planetary exploration, military actions, hazardou

Energy Benefits of Reconfigurable Hardware for Use in Underwater Sensor Nets

Small, dense underwater sensor networks have the potential to greatly improve undersea environmental and structural monitoring. However, few sensor nets exist because commercially available underwater acoustic modems are too costly and energy inefficient to be practical for this applications. Therefore, when designing an acoustic modem for sensor networks, the designer must optimize for low cost and low energy consumption at every level, from the analog electronics, to the signal processing scheme, to the hardware platform. In this paper we focus on the design choice of hardware platform: digital signal processors, microcontrollers, or reconfigurable hardware, to optimize for energy efficiency while keeping costs low. We implement one algorithm used in an acoustic modem design - matching pursuits for channel estimation - on all three platforms and perform a design space exploration to compare the timing, power and energy consumption of each implementation. We show that the reconfigurable hardware implementation can provide a maximum of 210 X and 52 X decrease in energy consumption over the microcontroller and DSP implementations respectively

Survey of Hardware Platforms for an Energy Efficient Implementation of Matching Pursuits Algorithm for Shallow Water Networks

Coral reefs worldwide are in serious decline. Underwater wireless sensor networks may be the answer to providing the persistent monitoring presence needed to obtain the data necessary to better understand how to protect these ecosystems for the future. Many advances have been made in underwater acoustic communication devices for underwater wireless sensor networks, but a major challenge that still remains is obtaining an energy efficient modem design. To begin to address this challenge, we implement the Matching Pursuits algorithm for channel estimation, an energy consuming portion of an existing underwater acoustic modem designed for shallow water networks, on a variety of hardware platforms. We determine that a dedicated field programmable gate array (FPGA) intellectual property core provides the most energy efficient hardware platform for Matching Pursuits which motivates future work to port the entire modem design to an FPGA for an energy efficient modem design

Architectural Optimization of Decomposition Algorithms for Wireless Communication Systems

Matrix decomposition is required in various algorithms used in wireless communication applications. FPGAs strike a balance between ASICs and DSPs, as they have the programmability of software with performance capacity approaching that of a custom hardware implementation. However, FPGA architectures require designers to make a countless number of system, architectural and logic design decisions. By performing design space exploration, a designer can find the optimal device for a specific application, however very few tools exist which can accomplish this task. This paper presents automatic generation and optimization of decomposition methods using a core generator tool, GUSTO, that we developed to enable easy design space exploration with different parameterization options such as resource allocation, bit widths of the data, number of functional units and organization of controllers and interconnects. We present a detailed study of area and throughput tradeoffs of matrix decomposition architectures using different parameterizations

Metric Rectification for Perspective Images of Planes

The main purpose of this survey is to understand completely the geometry, constraints and algorithmic implementation for metric rectification of planes. In this survey, I consider the perspective images and thus, using rectification helps me to measure metric properties from a perspective image. Additionally, because I consider perspective images, the concept of projective transformation is important. Thus, I start with defining the projective transformation. A projective transformation is a transformation which is used in projective geometry. I can say that it is the composition of a pair of perspective projections. It helps to understand the change of perceived positions of observed objects if the point of view of the observer changes. Projective transformation maps lines to lines, however it is not necessary to preserve parallelism. Here, it is important to state that projective transformations do not preserve sizes or angles but it preserves incidence and cross-ratio. These two preserved properties are very important i