High Performance Computing

For security, science, and society.

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High-Performance Computing

Advanced computing hardware and systems require advanced compilers. Learn more about our boutique solutions powered by decades of innovation.


Providing solutions based on rock solid, enterprise-class, high speed network sensing and spectral hypergraph analytics - using advanced algorithms and mathematics to give experts an advantage.


Based on breakthrough research, explore our suite of technologies addressing network flow optimization and packet path acceleration.



Our team has developed foundational technology in some of the most advanced compilers, commercial and open source, in use today.

Data Analytics

Cutting-edge hypergraph analysis technology for Big Data spanning security, finance, geospatial applications, and biology.


Advanced mathematics for new algorithms with asymptotic advantages, for problems in data analytics, sensing, and cognitive systems.

Recent Publications

An All–at–Once CP Decomposition Method for Count Tensors

CANDECOMP/PARAFAC (CP) tensor decomposition is a popular method for detecting latent behaviors in real– world data sets. As data sets grow larger and more elaborate, more sophisticated CP decomposition algorithms are required to enable these discoveries. Data sets from many applications can be represented as count tensors. To decompose count

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Filtered Tensor Construction and Decomposition for Drug Repositioning

Drug repositioning (also called “drug repurposing”) is a drug development strategy that saves time and money by finding new uses for existing drugs. While a variety of computational approaches to drug repositioning exist, recent work has shown that tensor decomposition, an unsupervised learning technique for finding latent structure in multidimensional

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