Minimizing synchronizations in sparse iterative solvers for distributed supercomputers

Eliminating synchronizations is one of the important techniques related to minimizing communications for modern high performance computing. This paper discusses principles of reducing communications due to global synchronizations in sparse iterative solvers on distributed supercomputers. We demonstrates how to minimizing global synchronizations by rescheduling a typical Krylov subspace method. The benefit of minimizing synchronizations is shown in theoretical analysis and is verified by numerical experiments using up to 900 processors. The experiments also show the communication complexity for some structured sparse matrix vector multiplications and global communications in the underlying supercomputers are in the order P1/2.5 and P4/5 respectively, where P is the number of processors and the experiments were carried on a Dawning 5000A

High-Throughput Computing on High-Performance Platforms: A Case Study

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan---a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner

MPWide: a light-weight library for efficient message passing over wide area networks

We present MPWide, a light weight communication library which allows efficient message passing over a distributed network. MPWide has been designed to connect application running on distributed (super)computing resources, and to maximize the communication performance on wide area networks for those without administrative privileges. It can be used to provide message-passing between application, move files, and make very fast connections in client-server environments. MPWide has already been applied to enable distributed cosmological simulations across up to four supercomputers on two continents, and to couple two different bloodflow simulations to form a multiscale simulation.Comment: accepted by the Journal Of Open Research Software, 13 pages, 4 figures, 1 tabl

Qualities of Grid Computing that can last for Ages

Grid computing has emerged as an important new field, distinguished from conventional distributed computing based on its abilities on large-scale resource sharing and services. And it will even become more popular because of the benefits it can offer over the traditional supercomputers, and other forms of distributed computing. This paper examines these benefits and also discusses why grid computing will continue toenjoy greater popularity and patronage in many years to come. Finally, we discussed about virtual organization (VO) as one of the key characteristics of Grid computing

Qualities of Grid Computing that can last for Ages

Grid computing has emerged as an important new field, distinguished from conventional distributed computing based on its abilities on large-scale resource sharing and services. And it will even become more popular because of the benefits it can offer over the traditional supercomputers, and other forms of distributed computing. This paper examines these benefits and also discusses why grid computing will continue toenjoy greater popularity and patronage in many years to come. Finally, we discussed about virtual organization (VO) as one of the key characteristics of Grid computing

Quality of service based data-aware scheduling

Distributed supercomputers have been widely used for solving complex computational problems and modeling complex phenomena such as black holes, the environment, supply-chain economics, etc. In this work we analyze the use of these distributed supercomputers for time sensitive data-driven applications. We present the scheduling challenges involved in running deadline sensitive applications on shared distributed supercomputers running large parallel jobs and introduce a ``data-aware\u27\u27 scheduling paradigm that overcomes these challenges by making use of Quality of Service classes for running applications on shared resources. We evaluate the new data-aware scheduling paradigm using an event-driven hurricane simulation framework which attempts to run various simulations modeling storm surge, wave height, etc. in a timely fashion to be used by first responders and emergency officials. We further generalize the work and demonstrate with examples how data-aware computing can be used in other applications with similar requirements

FooPar: A Functional Object Oriented Parallel Framework in Scala

We present FooPar, an extension for highly efficient Parallel Computing in the multi-paradigm programming language Scala. Scala offers concise and clean syntax and integrates functional programming features. Our framework FooPar combines these features with parallel computing techniques. FooPar is designed modular and supports easy access to different communication backends for distributed memory architectures as well as high performance math libraries. In this article we use it to parallelize matrix matrix multiplication and show its scalability by a isoefficiency analysis. In addition, results based on a empirical analysis on two supercomputers are given. We achieve close-to-optimal performance wrt. theoretical peak performance. Based on this result we conclude that FooPar allows to fully access Scala's design features without suffering from performance drops when compared to implementations purely based on C and MPI