An Automated Approach to Multidimensional Benchmarking on Large-Scale Systems

An adaptive modified firefly algorithm to unit commitment problem for large-scale power systems

Unit commitment (UC) problem tries to schedule output power of generation units to meet the system demand for the next several hours at minimum cost. UC adds a time dimension to the economic dispatch problem with the additional choice of turning generators to be on or off.  In this paper, in order to improve both the exploitation and exploration abilities of the firefly algorithm (FA), a new mo...

Automated Approach for Testing Large Scale Software

An Evaluation of Large-Scale Commercial Buildings Architectural Space Indicators with an Approach to Urban Threats and Risks

Abstract: Achieving to technical criteria that by applying them in architectural design stage of large commercial buildings, considered as one of the most important uses in urban planning, can increase the level of citizens’ security against all kinds of natural hazards and threats, and reduce vulnerability and it can provide continuation of the services and activities of these buildings. The p...

UNVEIL: A Large-Scale, Automated Approach to Detecting Ransomware

Although the concept of ransomware is not new (i.e., such attacks date back at least as far as the 1980s), this type of malware has recently experienced a resurgence in popularity. In fact, in the last few years, a number of high-profile ransomware attacks were reported, such as the large-scale attack against Sony that prompted the company to delay the release of the film “The Interview.” Ranso...

An Automated Benchmarking Toolset1

The drive for performance in parallel computing and the need to evaluate platform upgrades or replacements are major reasons frequent running of benchmark codes has become commonplace for application and platform evaluation and tuning. NIST is developing a prototype for an automated benchmarking toolset to reduce the manual effort in running and analyzing the results of such benchmarks. Our too...