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March 10, 2020
March 10, 2020
December 09, 2019
Over time, the definition of a tensor has varied across communities from mathematics to quantum physics. Lately, it has joined the machine learning community?s lexicon. If you search the web for the definition of a tensor, you will likely be overwhelmed by the varying explanations and heated discussions. In 1900, Gregorio Ricci Curbastro and his student Tullio Levi-Civita first published their theory of tensor calculus, which is also known as absolute differential calculus.
July 29, 2019
Modernizing a serial processing code to obtain optimal performance on an OpenVPX digital signal processing module - StoryMarch 12, 2018
Serial algorithms can be evolved to a scalable, multithreaded, multiprocess implementation using ubiquitous and well-established high-performance computing (HPC) programming frameworks such as OpenMP and MPI. Such techniques are used in compute-intensive defense, aerospace, and industrial applications.
September 18, 2017
The age-old debate regarding art versus science: Some engineers take a romantic approach, while others take a more traditional approach. Whether debugging is an art or a science or a combination of both will continue to be debated, but all sides can agree the tools can make all the difference between timely success and riding a metaphorical motorcycle down the road of failure.
Asking the right questions about HPEC software development tools for radar, SIGINT, and EW applications - StoryFebruary 06, 2017
High performance embedded computing (HPEC) system designers tasked with architecting large-scale supercomputer-class processing systems for radar, signal intelligence (SIGINT), and electronic warfare (EW) applications depend greatly on the software development tools available to them. The choice of development tools - such as debuggers, profilers, and cluster managers - can result in an intimate relationship; often the choice means the success or failure of the system design.
July 25, 2016
As parallel programming grows in importance and popularity, the critical challenge has become how to intelligently manage, develop, and debug the increasingly complex code. Traditional tools such as trace analysis, serial debuggers, and the venerable "printf"statement just aren't up to the task. Although some commercial off-the-shelf (COTS) vendors and customers in the embedded-defense space have attempted to develop their own parallel programming tools, the task has proved difficult and the resulting tools are far from full-featured. What's more, using proprietary development tools can add risk to a program's cost and schedule. The good news: A better source of tools for designing cutting-edge high-performance embedded computing (HPEC) systems already exists in an adjacent market - the commercial high-performance computing (HPC) market. Sourcing proven and powerful tools from the HPC community, long supported by an expansive user base, can greatly speed delivery time while decreasing costs and program risk.
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