Evaluating and Enabling Scalable High Performance Computing Workloads on Commercial Clouds

Performance, usability, and accessibility are critical components of high performance computing (HPC). Usability and performance are especially important to academic researchers as they generally have little time to learn a new technology and demand a certain type of performance in order to ensure the quality and quantity of their research results. We have observed that while not all workloads run well in the cloud, some workloads perform well. We have also observed that although commercial cloud adoption by industry has been growing at a rapid pace, its use by academic researchers has not grown as quickly. We aim to help close this gap and enable researchers to utilize the commercial cloud more efficiently and effectively. We present our results on architecting and benchmarking an HPC environment on Amazon Web Services (AWS) where we observe that there are particular types of applications that are and are not suited for the commercial cloud. Then, we present our results on architecting and building a provisioning and workflow management tool (PAW), where we developed an application that enables a user to launch an HPC environment in the cloud, execute a customizable workflow, and after the workflow has completed delete the HPC environment automatically. We then present our results on the scalability of PAW and the commercial cloud for compute intensive workloads by deploying a 1.1 million vCPU cluster. We then discuss our research into the feasibility of utilizing commercial cloud infrastructure to help tackle the large spikes and data-intensive characteristics of Transportation Cyberphysical Systems (TCPS) workloads. Then, we present our research in utilizing the commercial cloud for urgent HPC applications by deploying a 1.5 million vCPU cluster to process 211TB of traffic video data to be utilized by first responders during an evacuation situation. Lastly, we present the contributions and conclusions drawn from this work

Deletion of Glutamate Delta-1 Receptor in Mouse Leads to Aberrant Emotional and Social Behaviors

The delta family of ionotropic glutamate receptors consists of glutamate δ1 (GluD1) and glutamate δ2 (GluD2) receptors. While the role of GluD2 in the regulation of cerebellar physiology is well understood, the function of GluD1 in the central nervous system remains elusive. We demonstrate for the first time that deletion of GluD1 leads to abnormal emotional and social behaviors. We found that GluD1 knockout mice (GluD1 KO) were hyperactive, manifested lower anxiety-like behavior, depression-like behavior in a forced swim test and robust aggression in the resident-intruder test. Chronic lithium rescued the depression-like behavior in GluD1 KO. GluD1 KO mice also manifested deficits in social interaction. In the sociability test, GluD1 KO mice spent more time interacting with an inanimate object compared to a conspecific mouse. D-Cycloserine (DCS) administration was able to rescue social interaction deficits observed in GluD1 KO mice. At a molecular level synaptoneurosome preparations revealed lower GluA1 and GluA2 subunit expression in the prefrontal cortex and higher GluA1, GluK2 and PSD95 expression in the amygdala of GluD1 KO. Moreover, DCS normalized the lower GluA1 expression in prefrontal cortex of GluD1 KO. We propose that deletion of GluD1 leads to aberrant circuitry in prefrontal cortex and amygdala owing to its potential role in presynaptic differentiation and synapse formation. Furthermore, these findings are in agreement with the human genetic studies suggesting a strong association of GRID1 gene with several neuropsychiatric disorders including schizophrenia, bipolar disorder, autism spectrum disorders and major depressive disorder