The "IMP Science Gateway Portal" (http: scigate.imp.kiev.ua) for complex workflow management and inte- gration of distributed computing resources (like clusters, service grids, desktop grids, clouds) is presented. It is created on the basis of WS-PGRADE and gUSE technologies, where WS-PGRADE is designed for science workflow operation and gUSE - for smooth integration of available resources for parallel and distributed computing in various heterogeneous distributed computing infrastructures (DCI). The typical scientific workflow with possible scenarios of its preparation and usage is considered. Several typical science applications (scientific workflows) are considered for molecular dynamics (MD) simulations of complex behavior of various nanostructures (nanoindentation of graphene layers, defect system re- laxation in met al nanocrystals, thermal stability of boron nitride nanotubes, etc.). The advantages and drawbacks of the solution are shortly analyzed in the context of its practical applications for MD simulations in materials science, physics and nanotechnologies with available heterogeneous DCIs.
Several popular SG technologies are known for development of SG frameworks and instances, for example, WS-PGRADE gUSE DCI-bridge @cite_7 , ASKALON @cite_18 , MOTEUR @cite_16 , etc. They use different enabling components and technologies: web application containers (Tomcat, Glassfish, etc.), portal or web application frameworks (Liferay, Spring, Drupal, etc.), database management systems (MySQL, etc.), workflow management systems @cite_2 . Here the most promising SG framework, namely WS-PGRADE gUSE DCI-bridge bundle (which is an open-source project), is described with emphasize on some examples of its usage in several scientific communities like physics, materials science, nanotechnologies (Fig. ).
@cite_18 @cite_16 @cite_7 @cite_2
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An efficient exploitation of Distributed Computing Infrastructures (DCIs) is needed to deal with the data deluge that the scientific community is facing, in particular the Astrophysics one due to the emerging Square Kilometre Array (SKA) telescope that will reach data rates in the exascale domain. Hence, Science Gateways are being enriched with advanced tools that not only enable the scientists to build their experiments but also to optimize their adaptation to different infrastructures. In this work we present a method, called "two-level workflow system", to build this kind of tools and we apply it to a set of analysis tasks of interest for some use applications to the SKA. This method uses the Software-as-a-Service model to keep the scientists insulated from technical complexity of DCIs, and the COMPSs programming model to achieve an efficient use of the computing resources. The next-generation mobile network anticipates integrated heterogeneous fronthaul and backhaul technologies referred to as a unified crosshaul architecture. The crosshaul enables a flexible and cost-efficient infrastructure for handling mobile data tsunami from dense Internet of things (IoT). However, stabilization, energy efficiency, and latency have not been jointly considered in the optimization of crosshaul performance. To overcome these issues, we propose an orchestration scheme referred to as the stabilized green crosshaul orchestration (SGCO). SGCO utilizes a Lyapunov-theory-based drift-plus-penalty policy to determine the optimal amount of offloaded data that should be processed either at the eastbound or westbound computing platforms to minimize energy consumption. To achieve system stability, the cache buffer is considered as the main constraint in developing the optimization process. Moreover, the amount of offloaded data transmitted via crosshaul links is selected by adopting the binary min-knapsack problem. Accordingly, a lightweight heuristic algorithm is proposed. As the cache buffer is stabilized and the computations are controlled, the SGCO ensures adjustable computing latency threshold for various IoT services. The performance analysis shows that the proposed SGCO scheme exposes effective energy consumption compared to other existing schemes while maintaining system stability considering latency. Precise calculation of molecular electronic wavefunctions by methods such as coupled-cluster requires the computation of tensor contractions, the cost of which has polynomial computational scaling with respect to the system and basis set sizes. Each contraction may be executed via matrix multiplication on a properly ordered and structured tensor. However, data transpositions are often needed to reorder the tensors for each contraction. Writing and optimizing distributed-memory kernels for each transposition and contraction is tedious since the number of contractions scales combinatorially with the number of tensor indices. We present a distributed-memory numerical library (Cyclops Tensor Framework (CTF)) that automatically manages tensor blocking and redistribution to perform any user-specified contractions. CTF serves as the distributed-memory contraction engine in Aquarius, a new program designed for high-accuracy and massively-parallel quantum chemical computations. Aquarius implements a range of coupled-cluster and related methods such as CCSD and CCSDT by writing the equations on top of a C++ templated domain-specific language. This DSL calls CTF directly to manage the data and perform the contractions. Our CCSD and CCSDT implementations achieve high parallel scalability on the BlueGene Q and Cray XC30 supercomputer architectures showing that accurate electronic structure calculations can be effectively carried out on top of general distributed-memory tensor primitives. We introduce Cyclops Tensor Framework (CTF), a distributed-memory library for tensor contractions.CTF is able to perform tensor decomposition, redistribution, and contraction at runtime.CTF enables the expression of massively-parallel coupled-cluster methods via a concise tensor contraction interface.The quantum chemistry software suite Aquarius employs CTF to execute two coupled-cluster methods: CCSD and CCSDT.The Aquarius CCSD and CCSDT codes scale well on BlueGene Q and Cray XC30, comparing favorably to NWChem. Composite Web services (WS) can be seen as software systems designed according to workflow-based orchestration of building blocks or simpler WS. Each block has its own specifications concerning both functional and non-functional properties. While the characteristics of each block have a scope limited to its domain, the WS must guarantee service levels that are usually described by global end-to-end metrics. The problem of relating local to global objectives in WS orchestration is hard to approach. In this context, some WS components have to be deployed in distributed service oriented infrastructure mixing heterogeneous systems belonging to private and or public providers. In this paper we propose a performance-driven technique for designing and deploying composite WS on heterogeneous service oriented infrastructure. Users having different requirements in terms of resource demands and performance objectives are considered. Several WS deployment alternatives, involving both physical and virtual resources provided by the infrastructure, are evaluated to identify the logical (workflow) and physical (deployment) configuration allowing to meet the requirements. In order to demonstrate the suitability of the proposed approach to the service oriented context, an example of a travel management WS is described and the optimal deployment of the components in a hybrid infrastructure is investigated.