Publications
Measuring the impact of Spectre and Meltdown
Summary
Summary
The Spectre and Meltdown flaws in modern microprocessors represent a new class of attacks that have been difficult to mitigate. The mitigations that have been proposed have known performance impacts. The reported magnitude of these impacts varies depending on the industry sector and expected workload characteristics. In this paper, we...
Lessons learned from a decade of providing interactive, on-demand high performance computing to scientists and engineers
Summary
Summary
For decades, the use of HPC systems was limited to those in the physical sciences who had mastered their domain in conjunction with a deep understanding of HPC architectures and algorithms. During these same decades, consumer computing device advances produced tablets and smartphones that allow millions of children to interactively...
Detecting pathogen exposure during the non-symptomatic incubation period using physiological data
Summary
Summary
Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning based method to better detect asymptomatic states...
Bringing physical construction and real-world data collection into a massively open online course (MOOC)
Summary
Summary
This Work-In-Progress paper details the process and lessons learned when converting a hands-on engineering minicourse to a scalable, self-paced Massively Open Online Course (MOOC). Online courseware has been part of academic and industry training and learning for decades. Learning activities in online courses strive to mimic in-person delivery by including...
Benchmarking data analysis and machine learning applications on the Intel KNL many-core processor
Summary
Summary
Knights Landing (KNL) is the code name for the second-generation Intel Xeon Phi product family. KNL has generated significant interest in the data analysis and machine learning communities because its new many-core architecture targets both of these workloads. The KNL many-core vector processor design enables it to exploit much higher...
Detecting virus exposure during the pre-symptomatic incubation period using physiological data
Summary
Summary
Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning method to better detect asymptomatic states during...
Side channel authenticity discriminant analysis for device class identification
Summary
Summary
Counterfeit microelectronics present a significant challenge to commercial and defense supply chains. Many modern anti-counterfeit strategies rely on manufacturer cooperation to include additional identification components. We instead propose Side Channel Authenticity Discriminant Analysis (SICADA) to leverage physical phenomena manifesting from device operation to match suspect parts to a class of...
Benchmarking SciDB data import on HPC systems
Summary
Summary
SciDB is a scalable, computational database management system that uses an array model for data storage. The array data model of SciDB makes it ideally suited for storing and managing large amounts of imaging data. SciDB is designed to support advanced analytics in database, thus reducing the need for extracting...
Designing a new high performance computing education strategy for professional scientists and engineers
Summary
Summary
For decades the High Performance Computing (HPC) community has used web content, workshops and embedded HPC scientists to enable practitioners to harness the power of parallel and distributed computing. The most successful approaches, face-to-face tutorials and embedded professionals, don't scale. To create scalable, flexible, educational experiences for practitioners in all...
Scalability of VM provisioning systems
Summary
Summary
Virtual machines and virtualized hardware have been around for over half a century. The commoditization of the x86 platform and its rapidly growing hardware capabilities have led to recent exponential growth in the use of virtualization both in the enterprise and high performance computing (HPC). The startup time of a...