Enabling On-Demand Database Computing with MIT SuperCloud Database Management System

The MIT SuperCloud database management system allows for rapid creation and flexible execution of a variety of the latest scientific databases, including Apache Accumulo and SciDB. It is designed to permit these databases to run on a High Performance Computing Cluster (HPCC) platform as seamlessly as any other HPCC job. It ensures the seamless migration of the databases to the resources assigned by the HPCC scheduler and centralized storage of the database files when not running. It also permits snapshotting of databases to allow researchers to experiment and push the limits of the technology without concerns for data or productivity loss if the database becomes unstable.Comment: 6 pages; accepted to IEEE High Performance Extreme Computing (HPEC) conference 2015. arXiv admin note: text overlap with arXiv:1406.492

Lustre, Hadoop, Accumulo

Data processing systems impose multiple views on data as it is processed by the system. These views include spreadsheets, databases, matrices, and graphs. There are a wide variety of technologies that can be used to store and process data through these different steps. The Lustre parallel file system, the Hadoop distributed file system, and the Accumulo database are all designed to address the largest and the most challenging data storage problems. There have been many ad-hoc comparisons of these technologies. This paper describes the foundational principles of each technology, provides simple models for assessing their capabilities, and compares the various technologies on a hypothetical common cluster. These comparisons indicate that Lustre provides 2x more storage capacity, is less likely to loose data during 3 simultaneous drive failures, and provides higher bandwidth on general purpose workloads. Hadoop can provide 4x greater read bandwidth on special purpose workloads. Accumulo provides 10,000x lower latency on random lookups than either Lustre or Hadoop but Accumulo's bulk bandwidth is 10x less. Significant recent work has been done to enable mix-and-match solutions that allow Lustre, Hadoop, and Accumulo to be combined in different ways.Comment: 6 pages; accepted to IEEE High Performance Extreme Computing conference, Waltham, MA, 201

Melatonin for rapid eye movement sleep behavior disorder in Parkinson's disease : a randomised controlled trial

Background Melatonin may reduce REM-sleep behavior disorder (RBD) symptoms in Parkinson's disease (PD), though robust clinical trials are lacking. Objective To assess the efficacy of prolonged-release (PR) melatonin for RBD in PD. Methods Randomized, double-blind, placebo-controlled, parallel-group trial with an 8-week intervention and 4-week observation pre- and postintervention (ACTRN12613000648729). Thirty PD patients with rapid eye movement sleep behavior disorder were randomized to 4 mg of prolonged-release melatonin (Circadin) or matched placebo, ingested orally once-daily before bedtime. Primary outcome was the aggregate of rapid eye movement sleep behavior disorder incidents averaged over weeks 5 to 8 of treatment captured by a weekly diary. Data were included in a mixed-model analysis of variance (n = 15 per group). Results No differences between groups at the primary endpoint (3.4 events/week melatonin vs. 3.6 placebo; difference, 0.2; 95% confidence interval = -3.2 to 3.6; P = 0.92). Adverse events included mild headaches, fatigue, and morning sleepiness (n = 4 melatonin; n = 5 placebo). Conclusion Prolonged-release melatonin 4 mg did not reduce rapid eye movement sleep behavior disorder in PD. (c) 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society

Measuring the Impact of Spectre and Meltdown

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 measure the performance impact on several workloads relevant to HPC systems. We show that the impact can be significant on both synthetic and realistic workloads. We also show that the performance penalties are difficult to avoid even in dedicated systems where security is a lesser concern

Discovery of a Rich Cluster at z = 1.63 Using the Rest-frame 1.6 μm "Stellar Bump Sequence" Method

We present a new two-color algorithm, the "Stellar Bump Sequence" (SBS), that is optimized for robustly identifying candidate high-redshift galaxy clusters in combined wide-field optical and mid-infrared (MIR) data. The SBS algorithm is a fusion of the well-tested cluster red-sequence method of Gladders & Yee with the MIR 3.6 μm-4.5 μm cluster detection method developed by Papovich. As with the cluster red-sequence method, the SBS identifies candidate overdensities within 3.6 μm-4.5 μm color slices, which are the equivalent of a rest-frame 1.6 μm stellar bump "red-sequence." In addition to employing the MIR colors of galaxies, the SBS algorithm incorporates an optical/MIR (z'-3.6 μm) color cut. This cut effectively eliminates foreground 0.2 1.0 galaxies and add noise when searching for high-redshift galaxy overdensities. We demonstrate using the z ~ 1 GCLASS cluster sample that similar to the red sequence, the stellar bump sequence appears to be a ubiquitous feature of high-redshift clusters, and that within that sample the color of the stellar bump sequence increases monotonically with redshift and provides photometric redshifts accurate to Δz = 0.05. We apply the SBS method in the XMM-LSS SWIRE field and show that it robustly recovers the majority of confirmed optical, MIR, and X-ray-selected clusters at z > 1.0 in that field. Lastly, we present confirmation of SpARCS J022427-032354 at z = 1.63, a new cluster detected with the method and confirmed with 12 high-confidence spectroscopic redshifts obtained using FORS2 on the Very Large Telescope. We conclude with a discussion of future prospects for using the algorithm

Benchmarking SciDB Data Import on HPC Systems

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 data for analysis. It is designed to be massively parallel and can run on commodity hardware in a high performance computing (HPC) environment. In this paper, we present the performance of SciDB using simulated image data. The Dynamic Distributed Dimensional Data Model (D4M) software is used to implement the benchmark on a cluster running the MIT SuperCloud software stack. A peak performance of 2.2M database inserts per second was achieved on a single node of this system. We also show that SciDB and the D4M toolbox provide more efficient ways to access random sub-volumes of massive datasets compared to the traditional approaches of reading volumetric data from individual files. This work describes the D4M and SciDB tools we developed and presents the initial performance results. This performance was achieved by using parallel inserts, a in-database merging of arrays as well as supercomputing techniques, such as distributed arrays and single-program-multiple-data programming.Comment: 5 pages, 4 figures, IEEE High Performance Extreme Computing (HPEC) 2016, best paper finalis

The central policy unit in the governance of Hong Kong : a study of institutional dynamics

published_or_final_versionPolitics and Public AdministrationMasterMaster of Public Administratio

Evidence for the Universality of Properties of Red-sequence Galaxies in X-Ray- and Red-Sequence-Selected Clusters at z ~ 1

We study the slope, intercept, and scatter of the color–magnitude and color–mass relations for a sample of 10 infrared red-sequence-selected clusters at z ~ 1. The quiescent galaxies in these clusters formed the bulk of their stars above z ≳ 3 with an age spread Δt ≳ 1 Gyr. We compare UVJ color–color and spectroscopic-based galaxy selection techniques, and find a 15% difference in the galaxy populations classified as quiescent by these methods. We compare the color–magnitude relations from our red-sequence selected sample with X-ray- and photometric-redshift-selected cluster samples of similar mass and redshift. Within uncertainties, we are unable to detect any difference in the ages and star formation histories of quiescent cluster members in clusters selected by different methods, suggesting that the dominant quenching mechanism is insensitive to cluster baryon partitioning at z ~ 1