Supercomputing and Computation


1-10 of 179 Results

A Distribution Oblivious Scalable Approach for Large-Scale Scientific Data Processing
— Runtimes of scientific data processing (SDP) methods vary depending on data distribution characteristics, even when data size remains constant. A central issue in the scalable design of efficient large-scale SDP algorithms is the sensitivity of their execution times to data distribution. To gainfully utilize today’s massive computing infrastructures, a major challenge is to develop large-scale data processing capabilities that are independent of the underlying data distribution characteristics.

A Scalable Framework for Cyber Attack Discovery and Situational Understanding (SITU)
— yber attacks cost commercial and governmental organizations vast dollar amounts, result in stolen intellectual property, and reveal state secrets that endanger lives.

Abstract Scalable Performance Engineering Notation
— Aspen (Abstract Scalable Performance Engineering Notation) is a domain specific language for performance modeling that fills an important gap in existing techniques for performance prediction. It is designed to enable rapid exploration of new algorithms and architectures. It includes a formal specification of an application's performance behavior and an abstract machine model.

— The Adaptable IO System (ADIOS) is a parallel IO middleware designed for large-scale scientific simulations. The goal of this project is to provide fast, adaptable and scalable IO interfaces so that scientific codes can run highly efficiently across all computing platforms.

— The Adaptable IO System (ADIOS) was developed to provides a simple and flexible way to manage IO related tasks in large-scale and data-intensive scientific applications and it has been playing a central role in many real-world scientific applications, such as Gyrokinetic Toroidal Code (GTC), plasma fusion simulation code (XGC), combustion simulation code (S3D), etc.

Advanced Data Analysis Capability and Surrogate Generation
— Researchers rely on realistic datasets to build new analysis algorithms, but in many cases, realistic datasets have sensitivities that limit the audience that can work with them.

Advanced Security Acceleration Project for Smart Grid (ASAP-SG)
— The goal of this project is to develop a set of computer and network security requirements for the smart grid deployment. The key problem addressed in this project is to provide actionable security guidance to utilities for secure deployment of smart grid systems

Airport Viz – A 3D Tool to Enhance Security Operations
— Airport security personnel needed an easy-to-use tool to investigate passenger checkpoint designs, baggage inspection procedures, and SIDA operations.

An Ontology for the Simulation, Algorithms, and Modeling (SAM) Office of NA-22
— The Office of Nonproliferation and Verification R&D (NA-22) needs an ontology to support various activities including bibliographic annotation, modeling, and testing of detection algorithms

Analytics Cloud for Computational Analysis
— Provide world-class infrastructure and analytics for “Big Data” problems to enrich policy decision-makers in intelligence, defense for global security, transportation and finance.


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