JUSTGrid: a pure Java HPCC grid architecture for multi-physics solvers using complex geometries

After the Earth Simulator, built by NEC at the Japan Marine Science and Technology Centre (JAMSTEC) on an area of 3,250 m2 (50mx65m), began it's work in March 2002 with the outstanding performance of 35,860 Gflops (40 TFIops peak) [TRIOO], numerous scientists opted in favour of such a high-performance computation and communications (HPCC) approach, suggesting to build again Cray type vector supercomputers that dominated scientific computing in the mid seventies. Today (2009) the extended Earth Simulator has a peak performance of 131 TFIops but it was outperformed by several other systems with multi-core 1 architectures. Top 1 in June 2009 is the RoadRunner build by IBM for the DOE/NNSA/LANL with a peak performance of 1456 TFIops. Multi-core processors are now build in every PC for the consumer market and not only for HPC systems. It should be remembered that the computer games industry is responsible for the revolution in high end 3D graphics cards that convert any PC into a most powerful graphics workstation. It should be obvious, despite the computational power of the Earth Simulator, that this definitely is not the road of HPCC for general scientific and engineering computation. "I hope to concentrate my attention on my research rather then how to program", says Hitoshi Sakagami, a researcher at Japan's Himeji Institute of Technology and a Gordon Bell Prize finalist for work using the Earth Simulator [TRIOO]. I fully agree with this statement, and this is one of the major reasons that I have chosen Java as high performance computing language. Programming vector computers is a difficult task, and to obtain acceptable results with regard to announced peak performance has been notoriously cumbersome. On the other hand, multi-core systems with many processors on a single chip need to be programmed in a different, namely a multi threaded way. Threads are a substantial part of the Java programming language. Java is the only general programming language that does not need external libraries for parallel programming, because everything needed is built into the language. In addition, there are major additional advantages of the Java language (object oriented, parallelization, readability, maintainability, programmer productivity, platform independence, code safety and reliability, database connectivity, internet capability, multimedia capability, GUI (graphics user interfaces), 3D graphics (Java 3D) and portability etc.) which were discussed in this thesis. The objective of this work is to build an easy to use software framework for high performance computing dealing with complex 3D geometries. The framework should also take care of all the advantages and behaviours of modern multi-core/multi-threaded hardware architectures. In view of the increasing complexity of modern hardware, working on solutions of multi-physical problems demands for software, that makes the solving process mostly independent of the available machinery

A Pure Java Parallel Flow Solver

In this paper an overview is given on the "Have Java" project to attain a pure Java parallel Navier-Stokes flow solver (JParNSS) based on the thread concept and remote method invocation (RMI). The goal of this project is to produce an industrial flow solver running on an arbitrary sequential or parallel architecture, utilizing the Internet, capable of handling the most complex 3D geometries as well as flow physics, and also linking to codes in other areas such as aeroelasticity etc. Since Java is completely object-oriented the code has been written in an object-oriented programming (OOP) style. The code also includes a graphics user interface (GUI) as well as an interactive steering package for the parallel architecture. The Java OOP approach provides profoundly improved software productivity, robustness, and security as well as reusability and maintainability. OOP allows code construction similar to the aerodynamic design process because objects can be software coded and integrated, reflecting actual design procedures. In addition, Java is the programming language of the Internet and thus Java is the programming language of the Internet and thus Java objects on disparate machines or even separate networks can be connected. We explain the motivation for the design of JParNSS along with its capabilities that set it apart from other solvers. In the first two sections we present a discussion of the Java language as the programming tool for aerospace applications. In section three the objectives of the Have Java project are presented. In the next section the layer structures of JParNSS are discussed with emphasis on the parallelization and client-server (RMI) layers. JParNSS, like its predecessor ParNSS (ANSI-C), is based on the multiblock idea, and allows for arbitrarily complex topologies. Grids are accepted in GridPro property settings, grids of any size or block number can be directly read by JParNSS without any further modifications, requiring no additional preparation time for the solver input. In the last section, computational results are presented, with emphasis on multiprocessor Pentium and Sun parallel systems run by the Solaris operating system (OS)

A Test Suite for High-Performance Parallel Java

The Java programming language has a number of features that make it attractive for writing high-quality, portable parallel programs. A pure object formulation, strong typing and the exception model make programs easier to create, debug, and maintain. The elegant threading provides a simple route to parallelism on shared-memory machines. Anticipating great improvements in numerical performance, this paper presents a suite of simple programs that indicate how a pure Java Navier-Stokes solver might perform. The suite includes a parallel Euler solver. We present results from a 32-processor Hewlett-Packard machine and a 4-processor Sun server. While speedup is excellent on both machines, indicating a high-quality thread scheduler, the single-processor performance needs much improvement

New mechanistic insights, novel treatment paradigms, and clinical progress in cerebrovascular diseases

The past decade has brought tremendous progress in diagnostic and therapeutic options for cerebrovascular diseases as exemplified by the advent of thrombectomy in ischemic stroke, benefitting a steeply increasing number of stroke patients and potentially paving the way for a renaissance of neuroprotectants. Progress in basic science has been equally impressive. Based on a deeper understanding of pathomechanisms underlying cerebrovascular diseases, new therapeutic targets have been identified and novel treatment strategies such as pre- and post-conditioning methods were developed. Moreover, translationally relevant aspects are increasingly recognized in basic science studies, which is believed to increase their predictive value and the relevance of obtained findings for clinical application.This review reports key results from some of the most remarkable and encouraging achievements in neurovascular research that have been reported at the 10th International Symposium on Neuroprotection and Neurorepair. Basic science topics discussed herein focus on aspects such as neuroinflammation, extracellular vesicles, and the role of sex and age on stroke recovery. Translational reports highlighted endovascular techniques and targeted delivery methods, neurorehabilitation, advanced functional testing approaches for experimental studies, pre-and post-conditioning approaches as well as novel imaging and treatment strategies. Beyond ischemic stroke, particular emphasis was given on activities in the fields of traumatic brain injury and cerebral hemorrhage in which promising preclinical and clinical results have been reported. Although the number of neutral outcomes in clinical trials is still remarkably high when targeting cerebrovascular diseases, we begin to evidence stepwise but continuous progress towards novel treatment options. Advances in preclinical and translational research as reported herein are believed to have formed a solid foundation for this progress

Contrast-enhanced ultrasonography characteristics of intrathoracic mass lesions in 36 dogs and 24 cats

Contrast-enhanced ultrasonography (CEUS) is increasingly available for veterinary patients, however limited studies describe the use of this method for characterizing intrathoracic mass lesions. The aim of this prospective, observational study was to describe CEUS enhancement patterns for intrathoracic mass lesions in a sample of cats and dogs. Sixty patients (36 dogs, 24 cats) were included. Standardized CEUS examinations were performed for 41 pulmonary masses (68%) and 19 mediastinal masses (32%). Final diagnosis was based on cytology and/or histopathology. Absolute time to enhancement (TTE) values were recorded for the intrathoracic mass lesions and spleen. The spleen was used as a reference parenchymal organ to calculate relative TTE (rTTE) values. Absolute TTE of the spleen and intrathoracic mass lesions differed for dogs and cats (P = 0.001). The rTTE values significantly differed between lesions of neoplastic versus non-neoplastic origin (P = 0.004). The majority of neoplastic pulmonary masses were supplied by bronchial arteries (63%), while most nonneoplastic pulmonary masses were supplied by pulmonary arteries (78%). The sensitivity and specificity for detecting pulmonary neoplastic masses with rTTE were 63% and 78%, respectively. Enhancement patterns for mediastinal thymomas and lymphomas significantly differed (P = 0.002). Thymomas enhanced heterogeneously in a centripetal pattern (86%), whereas lymphomas typically enhanced uniformly in a centrifugal pattern (75%). Findings indicated that CEUS is a feasible method for characterizing intrathoracic mass lesions in dogs and cats, however, the diagnostic sensitivity for detecting neoplastic pulmonary masses was low