FPGA Reliability
Ease of reconfigurability combined with recent increase in logic density and speed of FPGA chips have encouraged designers to take advantage of FPGAs and extend their role as computing elements in lieu of ASICs. However, the use of FPGA chips in specialized applications may give rise to failures that could have a significant impact on the security and dependability of those applications. With the number of FPGA applications on the rise and the wide usage of FPGAs in mission critical applications, understanding the causes and effects of FPGA faults has become very crucial.
In this research program we investigate the causes of application failures that are unique to FPGAs with a view toward the development of design practices for minimizing their impact. We are taking a systems' approach toward the identification of faults and the establishment of design criteria for improving the dependability of FPGAs. We undertake a comprehensive examination of the entire lifecycle of FPGA designs starting from the chip design and fabrication to the configuration and operation of FPGA-based design. In addition, the entire design process is examined as a whole in order to identify critical activities and sequences of these activities.
During the current phase of the project we plan to investigate the failure modes of FPGAs and the factors that contribute to their occurrence, including design practices and tools. This phase will be concluded with the development of criteria and/or metrics for measuring the impact of each failure mode. Such metrics combined with the general classification of the FPGA faults and the frequency of their occurrence will enable the development of a ranked list of faults based on their criticality in order to enable the development of high impact.
DARPA HPCS - Ultraviolet Project
In an effort to boost high-performance computing users productivity and cut time-to-solution, which is a function of development time and execution time, Silicon Graphics, along with the George Washington University, the Massachusetts Institute of Technology, University of Minnesota, and the University of Utah; have been conceiving novel computing architectures and programming models for a next generation advanced computer system. The final outcome will be the first commercial peta-scale super computer, the Ultraviolet, which can be deployed by 2010. Funding for this project is provided through DARPA’s high-productivity computing systems(HPCS) program, Phase I.
IP Tools
The emergence of intellectual property components has caused a redefinition of the field of embedded systems. Many modern embedded systems are defined as multi-chip modules (MCMs) or System on a Chip (SoC) designs composed of IP components from a variety of vendors. Engineers often spend a significant portion of time reviewing IP components for suitability to their respective embedded system design. This process considers a myriad of permutations before the final components are selected. This task seeks to answer the following questions:
- What IP component attributes distinguish each from the other?
- Can these attributes be specified in a general manner such that they may be applied to a finite sized set of disparate IP components?
- Is there a clear an unambiguous methodology to categorize IP components?
- Is it possible to develop an automated tool that anneals over various categories of IP components to yield an optimal composition set (OCS)?
Effective Use of Distributed Reconfigurable Computing Resources
While the number of reconfigurable computing resources available on computer networks has been growing rapidly in recent years, within an organization or across federated organizations, these systems are still expensive compared to commodity workstations. Therefore, it is important to try to maximize their utilization. This project establishes the middleware needed for monitoring, aggregating, and scheduling reconfigurable resources for shared use in a grid-computing style. In doing so, the team has investigated and extended Job Management Systems (JMSs) to recognize, monitor, and schedule reconfigurable computing resources over the network. A prototype using LSF has been established and successfully used.
Remote Sensing
Hyperspectral remote sensing sensors are capable of collecting remote sensing imagery at several hundred bands over the spectrum. Under these advanced observation tools, the observed phenomena can be identified with unique signatures, however, the resulting data volumes are quite massive. Processing hyperspectral data using new efficient techniques and architectures is therefore very critical.
Our advanced hyperspectral processing falls into three different areas;
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- Investigating high-performance algorithms for dimension reduction of hypersepctral data based on methods such as Principal Component Analysis (PCA), Projection Pursuit, and Wavelet analysis.
- Investigating high-performance algorithms for remote sending data fusion.
- Investigating reconfigurable computer architectures for satellite onboard processing of hyperspectral imagery for dimension reduction and cloud detection
Reconfigurable Computing Library
The synergistic advances in high-performance computing systems and in reconfigurable computing, based on field programmable gate arrays (FPGAs), form the basis for a new paradigm shift in supercomputing, namely reconfigurable supercomputing. This can be achieved through hybrid systems of microprocessors as well as FPGA modules. Such systems inherently support both fine-grain and coarse-grain parallelism, and can tune their architectures to fit the needs of applications.
While our objective is to pursue the aforementioned concepts in general, the objectives of our current project are to:
- Accelerate the development of parallel reconfigurable computers based on the Starbridge and SRC architectures,
- Validate the concepts through useful application developments, testing and benchmarking with focus on the security area,
- Iintegrate the experience of the research community and views of industry, academia and government research scientists. Our application areas currently focus on cryptography applications