807 research outputs found
Many-Task Computing and Blue Waters
This report discusses many-task computing (MTC) generically and in the
context of the proposed Blue Waters systems, which is planned to be the largest
NSF-funded supercomputer when it begins production use in 2012. The aim of this
report is to inform the BW project about MTC, including understanding aspects
of MTC applications that can be used to characterize the domain and
understanding the implications of these aspects to middleware and policies.
Many MTC applications do not neatly fit the stereotypes of high-performance
computing (HPC) or high-throughput computing (HTC) applications. Like HTC
applications, by definition MTC applications are structured as graphs of
discrete tasks, with explicit input and output dependencies forming the graph
edges. However, MTC applications have significant features that distinguish
them from typical HTC applications. In particular, different engineering
constraints for hardware and software must be met in order to support these
applications. HTC applications have traditionally run on platforms such as
grids and clusters, through either workflow systems or parallel programming
systems. MTC applications, in contrast, will often demand a short time to
solution, may be communication intensive or data intensive, and may comprise
very short tasks. Therefore, hardware and software for MTC must be engineered
to support the additional communication and I/O and must minimize task dispatch
overheads. The hardware of large-scale HPC systems, with its high degree of
parallelism and support for intensive communication, is well suited for MTC
applications. However, HPC systems often lack a dynamic resource-provisioning
feature, are not ideal for task communication via the file system, and have an
I/O system that is not optimized for MTC-style applications. Hence, additional
software support is likely to be required to gain full benefit from the HPC
hardware
O2ATH: An OpenMP Offloading Toolkit for the Sunway Heterogeneous Manycore Platform
The next generation Sunway supercomputer employs the SW26010pro processor,
which features a specialized on-chip heterogeneous architecture. Applications
with significant hotspots can benefit from the great computation capacity
improvement of Sunway many-core architectures by carefully making intensive
manual many-core parallelization efforts. However, some legacy projects with
large codebases, such as CESM, ROMS and WRF, contain numerous lines of code and
do not have significant hotspots. The cost of manually porting such
applications to the Sunway architecture is almost unaffordable. To overcome
such a challenge, we have developed a toolkit named O2ATH. O2ATH forwards GNU
OpenMP runtime library calls to Sunway's Athread library, which greatly
simplifies the parallelization work on the Sunway architecture.O2ATH enables
users to write both MPE and CPE code in a single file, and parallelization can
be achieved by utilizing OpenMP directives and attributes. In practice, O2ATH
has helped us to port two large projects, CESM and ROMS, to the CPEs of the
next generation Sunway supercomputers via the OpenMP offload method. In the
experiments, kernel speedups range from 3 to 15 times, resulting in 3 to 6
times whole application speedups.Furthermore, O2ATH requires significantly
fewer code modifications compared to manually crafting CPE functions.This
indicates that O2ATH can greatly enhance development efficiency when porting or
optimizing large software projects on Sunway supercomputers.Comment: 15 pages, 6 figures, 5 tables
Implementation and scaling of the fully coupled Terrestrial Systems Modeling Platform (TerrSysMP) in a massively parallel supercomputing environment – a case study on JUQUEEN (IBM Blue Gene/Q)
Continental-scale hyper-resolution simulations constitute a grand challenge in characterizing non-linear feedbacks of states and fluxes of the coupled water, energy, and biogeochemical cycles of terrestrial systems. Tackling this challenge requires advanced coupling and supercomputing technologies for earth system models that are discussed in this study, utilizing the example of the implementation of the newly developed Terrestrial Systems Modeling Platform (TerrSysMP) on JUQUEEN (IBM Blue Gene/Q) of the Jülich Supercomputing Centre, Germany. The applied coupling strategies rely on the Multiple Program Multiple Data (MPMD) paradigm and require memory and load balancing considerations in the exchange of the coupling fields between different component models and allocation of computational resources, respectively. These considerations can be reached with advanced profiling and tracing tools leading to the efficient use of massively parallel computing environments, which is then mainly determined by the parallel performance of individual component models. However, the problem of model I/O and initialization in the peta-scale range requires major attention, because this constitutes a true big data challenge in the perspective of future exa-scale capabilities, which is unsolved
The Data Fusion Grid Infrastructure: Project Objectives and Achievements
This paper describes the objectives and achievements of the project "Data Fusion Grid Infrastructure'' jointly supported by INTAS, the Centre National d'Etudes Spatiales (CNES) and the National Space Agency of Ukraine (NSAU). Within the project, a Grid infrastructure has been developed that integrates the resources of several geographically distributed organizations. The use of Grid technologies is motivated by the need to make computations in the near real-time for fast response to natural disasters and to manage large volumes of satellite data. We show the use of developed Grid infrastructure for a number of applications that heavily rely on Earth observation (EO) data. These applications include: numerical weather prediction (NWP), flood monitoring, biodiversity assessment, and crop yield prediction
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