An Application-Based Performance Evaluation of NASAs Nebula Cloud Computing Platform

The high performance computing (HPC) community has shown tremendous interest in exploring cloud computing as it promises high potential. In this paper, we examine the feasibility, performance, and scalability of production quality scientific and engineering applications of interest to NASA on NASA's cloud computing platform, called Nebula, hosted at Ames Research Center. This work represents the comprehensive evaluation of Nebula using NUTTCP, HPCC, NPB, I/O, and MPI function benchmarks as well as four applications representative of the NASA HPC workload. Specifically, we compare Nebula performance on some of these benchmarks and applications to that of NASA s Pleiades supercomputer, a traditional HPC system. We also investigate the impact of virtIO and jumbo frames on interconnect performance. Overall results indicate that on Nebula (i) virtIO and jumbo frames improve network bandwidth by a factor of 5x, (ii) there is a significant virtualization layer overhead of about 10% to 25%, (iii) write performance is lower by a factor of 25x, (iv) latency for short MPI messages is very high, and (v) overall performance is 15% to 48% lower than that on Pleiades for NASA HPC applications. We also comment on the usability of the cloud platform

Expanding a Supercomputer Facility Using Modular Data Center Technology

With the expansion of high-end computing resources needed to support NASA's increasing demands for physics-based simulations, the facility housing Pleiades-the agency's largest supercomputer-recently reached its power and cooling capacity. In response, the NASA Advanced Supercomputing Division at Ames Research Center undertook a prototype project that resulted in a new facility based on modular data center technology. The facility, a ~1000 square-foot module on a concrete pad with room for 16-18 compute racks, was completed in fall 2016 and an SGI computer system, named Electra, was deployed there in early 2017. Cooling is performed via an evaporative system built into the module, and preliminary experience shows a Power Usage Effectiveness (PUE) of ~1.03. Electra achieved over a petaflop on the LINPACK benchmark, sufficient to rank number 96 on the November 2016 TOP500 list. The system consists of 1,152 InfiniBand-connected Intel Xeon Broadwell-based nodes. Its users access their files on a facility wide file system shared by all compute assets via Mellanox MetroX InfiniBand extenders, which connect the Electra fabric to Lustre routers InfiniBand fabric over fiber-optic links about 300 meters long. The prototype has exceeded expectations and is serving as a blueprint for future expansions.

Evaluating the Suitability of Commercial Clouds for NASA's High Performance Computing Applications: A Trade Study

NASAs High-End Computing Capability (HECC) Project is periodically asked if it could be more cost effective through the use of commercial cloud resources. To answer the question, HECCs Application Performance and Productivity (APP) team undertook a performance and cost evaluation comparing three domains: two commercial cloud providers, Amazon and Penguin, and HECCs in-house resourcesthe Pleiades and Electra systems. In the study, the APP team used a combination of the NAS Parallel Benchmarks (NPB) and six full applications from NASAs workload on Pleiades and Electra to compare performance of nodes based on three different generations of Intel Xeon processorsHaswell, Broadwell, and Skylake. Because of export control limitations, the most heavily used applications on Pleiades and Electra could not be used in the cloud; therefore, only one of the applications, OpenFOAM, represents work from the Aeronautics Research Mission Directorate and the Human and Exploration Mission Directorate. The other five applications are from the Science Mission Directorate

Measurements of Differential Reflectivity in Snowstorms and Warm Season Stratiform Systems

The organized behavior of differential radar reflectivity (ZDR) is documented in the cold regions of a wide variety of stratiform precipitation types occurring in both winter and summer. The radar targets and attendant cloud microphysical conditions are interpreted within the context of measurements of ice crystal types in laboratory diffusion chambers in which humidity and temperature are both stringently controlled. The overriding operational interest here is in the identification of regions prone to icing hazards with long horizontal paths. Two predominant regimes are identified: category A, which is typified by moderate reflectivity (from 10 to 30 dBZ) and modest +ZDR values (from 0 to +3 dB) in which both supercooled water and dendritic ice crystals (and oriented aggregates of ice crystals) are present at a mean temperature of −13°C, and category B, which is typified by small reflectivity (from −10 to +10 dBZ) and the largest +ZDR values (from +3 to +7 dB), in which supercooled water is dilute or absent and both flat-plate and dendritic crystals are likely. The predominant positive values for ZDR in many case studies suggest that the role of an electric field on ice particle orientation is small in comparison with gravity. The absence of robust +ZDR signatures in the trailing stratiform regions of vigorous summer squall lines may be due both to the infusion of noncrystalline ice particles (i.e., graupel and rimed aggregates) from the leading deep convection and to the effects of the stronger electric fields expected in these situations. These polarimetric measurements and their interpretations underscore the need for the accurate calibration of ZDR.United States. Federal Aviation Administration (Air Force Contract FA8721-05-C-0002

A wellness study of 108 individuals using personal, dense, dynamic data clouds.

Personal data for 108 individuals were collected during a 9-month period, including whole genome sequences; clinical tests, metabolomes, proteomes, and microbiomes at three time points; and daily activity tracking. Using all of these data, we generated a correlation network that revealed communities of related analytes associated with physiology and disease. Connectivity within analyte communities enabled the identification of known and candidate biomarkers (e.g., gamma-glutamyltyrosine was densely interconnected with clinical analytes for cardiometabolic disease). We calculated polygenic scores from genome-wide association studies (GWAS) for 127 traits and diseases, and used these to discover molecular correlates of polygenic risk (e.g., genetic risk for inflammatory bowel disease was negatively correlated with plasma cystine). Finally, behavioral coaching informed by personal data helped participants to improve clinical biomarkers. Our results show that measurement of personal data clouds over time can improve our understanding of health and disease, including early transitions to disease states

The XMM Cluster Survey: testing chameleon gravity using the profiles of clusters

The chameleon gravity model postulates the existence of a scalar field that couples with matter to mediate a fifth force. If it exists, this fifth force would influence the hot X-ray emitting gas filling the potential wells of galaxy clusters. However, it would not influence the clusters weak lensing signal. Therefore, by comparing X-ray and weak lensing profiles, one can place upper limits on the strength of a fifth force. This technique has been attempted before using a single, nearby cluster (Coma, z = 0.02). Here we apply the technique to the stacked profiles of 58 clusters at higher redshifts (0.1 < z < 1.2), including 12 new to the literature, using X-ray data from the XMM Cluster Survey and weak lensing data from the Canada-France-Hawaii-Telescope Lensing Survey. Using a multiparameter Markov chain Monte Carlo analysis, we constrain the two chameleon gravity parameters (beta and phi∞). Our fits are consistent with general relativity, not requiring a fifth force. In the special case of f(R) gravity (where beta = &surd;{1/6}), we set an upper limit on the background field amplitude today of |fR0| < 6 × 10-5 (95 per cent CL). This is one of the strongest constraints to date on |fR0| on cosmological scales. We hope to improve this constraint in future by extending the study to hundreds of clusters using data from the Dark Energy Survey

Lack of association between HLA antigen DR3 and α<inf>1</inf> deficiency in liver transplant recipients

The relationship between α1-antitrypsin deficiency (α-ATD) and the HLA antigen system was studied in 32 liver transplant recipients. Despite previous reports of an association of HLA antigen DR3 with homozygosity for α-AT ZZ, no such association was seen in this population of α-ATD homozygous ZZ patients with advanced hepatic disease. Thus, the reported association of HLA class II antigens and homozygosity for the Z allele for α-AT may be an artifact of either a small study population or geographic inbreeding and a coincidental association of certain HLA antigens with the presence of homozygosity for the Z allele of α-AT. © 1993 Plenum Publishing Corporation

Measuring the capability to raise revenue process and output dimensions and their application to the Zambia revenue authority

The worldwide diffusion of the good governance agenda and new public management has triggered a renewed focus on state capability and, more specifically, on the capability to raise revenue in developing countries. However, the analytical tools for a comprehensive understanding of the capability to raise revenue remain underdeveloped. This article aims at filling this gap and presents a model consisting of the three process dimensions ‘information collection and processing’, ‘merit orientation’ and ‘administrative accountability’. ‘Revenue performance’ constitutes the fourth capability dimension which assesses tax administration’s output. This model is applied to the case of the Zambia Revenue Authority. The dimensions prove to be valuable not only for assessing the how much but also the how of collecting taxes. They can be a useful tool for future comparative analyses of tax administrations’ capabilities in developing countries.Die weltweite Verbreitung der Good-Governance- und New-Public-Management-Konzepte hat zu einer zunehmenden Konzentration auf staatliche Leistungsfähigkeit und, im Besonderen, auf die Leistungsfähigkeit der Steuererhebung in Entwicklungsländern geführt. Allerdings bleiben die analytischen Werkzeuge für ein umfassendes Verständnis von Leistungsfähigkeit unterentwickelt. Dieser Artikel stellt hierfür ein Modell vor, das die drei Prozess-Dimensionen „Sammeln und Verarbeiten von Informationen“, „Leistungsorientierung der Mitarbeiter“ und „Verantwortlichkeit der Verwaltung“ beinhaltet. „Einnahmeperformanz“ ist die vierte Dimension und erfasst den Output der Steuerverwaltung. Das mehrdimensionale Modell wird für die Analyse der Leistungsfähigkeit der Steuerbehörde Zambias (Zambia Revenue Authority) genutzt. Es erweist sich nicht nur für die Untersuchung des Wieviel, sondern auch des Wie des Erhebens von Steuern als wertvoll. Die vier Dimensionen können in Zukunft zur umfassenden und vergleichenden Analyse der Leistungsfähigkeit verschiedener Steuerverwaltungen in Entwicklungsländern genutzt werden

Classification of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics

IMPORTANCE: Despite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics. OBJECTIVE: To develop and characterize a gross morphologic classification system for HGSOC. DESIGN, SETTING, AND PARTICIPANTS: This cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of HGSOC. Researchers assigning morphologic subtype and performing molecular analyses were blinded to clinical outcomes. Data analysis was performed between April 2020 and November 2021. EXPOSURES: Gross tumor morphologic characteristics. MAIN OUTCOMES AND MEASURES: Clinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared. RESULTS: Of 112 women (mean [SD] age 62.7 [9.7] years) included in the study, most patients (84% [94]) exhibited a predominant morphologic subtype and many (63% [71]) had a uniform morphologic subtype at all involved sites. Compared with those with uniform type I morphologic subtype, patients with uniform type II morphologic subtype were more likely to have a favorable Fagotti score (83% [19 of 23] vs 46% [22 of 48]; P = .004) and thus to be triaged to primary tumor reductive surgery. Similarly, patients with uniform type II morphologic subtype also had significantly higher mean (SD) estimated blood loss (639 [559; 95% CI, 391-887] mL vs 415 [527; 95% CI, 253-577] mL; P = .006) and longer mean (SD) operative time (408 [130; 95% CI, 350-466] minutes vs 333 [113; 95% CI, 298-367] minutes; P = .03) during tumor reductive surgery. Type I tumors had enrichment of epithelial-mesenchymal transition (false discovery rate [FDR] q-value, 3.10 × 10-24), hypoxia (FDR q-value, 1.52 × 10-5), and angiogenesis pathways (FDR q-value, 2.11 × 10-2), whereas type II tumors had enrichment of pathways related to MYC signaling (FDR q-value, 2.04 × 10-9) and cell cycle progression (FDR q-value, 1.10 × 10-5) by integrated proteomic and transcriptomic analysis. Abundances of metabolites and lipids also differed between the 2 morphologic subtypes. CONCLUSIONS AND RELEVANCE: This study identified 2 novel, gross morphologic subtypes of HGSOC, each with unique clinical features and molecular signatures. The findings may have implications for triaging patients to surgery or chemotherapy, identifying outcomes, and developing tailored therapeutic strategies