Increase in intensive applications with different computational requirements, coupled with the unification of remote and diverse resources thanks to advances in the wide-area network technologies and the low cost of c...
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ISBN:
(纸本)9780769527840
Increase in intensive applications with different computational requirements, coupled with the unification of remote and diverse resources thanks to advances in the wide-area network technologies and the low cost of components, have-encouraged the development of grid computing. To exploit the promising potentials of geographically distributed resources, effective and efficient mapping algorithms are fundamental. Since the problem of optimally mapping is NP-complete, the development of evolutionary techniques to find near-optimal solutions is welcome. In this paper a distributed system based on Differential Evolution is designed and implemented to face the mapping problem in a gild environment aiming at reducing the degree of use of the grid resources. This system is tested on some different resource allocation scenarios.
Built from a need for modelling cognitive processes, a modular neural network is designed as the "brain" of a virtual robot moving in a prey-predator environment. The robot decides its path from the animals ...
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Built from a need for modelling cognitive processes, a modular neural network is designed as the "brain" of a virtual robot moving in a prey-predator environment. The robot decides its path from the animals it identifies around. Both a parallel implementation of distributed processes and a temporal coding of spiking neurons allow the robot to develop multimodal' perception with attentional mechanisms and to react in real-time to its dynamic environment.
The study discusses challenges in deploying Artificial Intelligence (AI) on Internet-of-Things (IoT) devices and introduces a solution called Adaptive Offloading Point (AOP) for Federated Learning (FL) in Edge AI. AOP...
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Extreme-scale applications (i.e., Big-Compute) are becoming increasingly data-intensive, i.e., producing and consuming increasingly large amounts of data. The HPC systems traditionally used for these applications are ...
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ISBN:
(纸本)9781538649756
Extreme-scale applications (i.e., Big-Compute) are becoming increasingly data-intensive, i.e., producing and consuming increasingly large amounts of data. The HPC systems traditionally used for these applications are now used for Big-Data applications such as data analytics, social network analysis, machine learning, and genomics. As a consequence of these trends, the system architecture should be flexible and data-centric. This can already be witnessed in the pre-exascale systems with TBs of on-node hierarchical and heterogeneous memories, PBs of system memory, low-latency, high-throughput networks, and many threaded cores. As such, the pre-exascale systems suit the needs of both Big-Compute and Big-Data applications. Though the system architecture is flexible enough to support both Big-Compute and Big-Data, we argue there is a software gap. Particularly, we need data-centric abstractions to leverage the full potential of the system, i.e., there is a need for native support for data resilience, the ability to express data locality and affinity, mechanisms to reduce data movement, the ability to share data, and abstractions to express User's data usage and data access patterns. In this paper, we (i) show the need for taking a holistic approach towards data-centric abstractions, (ii) show how these approaches were realized in the SHARed data-structure centric Programming abstraction (SharP) library, a data-structure centric programming abstraction, and (iii) apply these approaches to a variety of applications that demonstrate its usefulness. Particularly, we apply these approaches to QMCPack and the Graph500 benchmark and demonstrate the advantages of this approach on extreme-scale systems.
In existing meeting scheduling systems, finding a common free time slot of all (prospective) participants is the goal. When such a free time slot is not found, the host has to ask the busy participants to change their...
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In existing meeting scheduling systems, finding a common free time slot of all (prospective) participants is the goal. When such a free time slot is not found, the host has to ask the busy participants to change their schedules. Changing a schedule is a complex process requiring a lot of negotiations and, there is no guarantee that the goal will be achieved. In the worst case, the host has to ignore the time slot (which was probably the first choice) and try to schedule the meeting in another time slot (probably a lesser choice). The process will continue till the scheduling succeeds. We argue that it is not always necessary for all the participants to attend a meeting. There are some participants whose presence is mandatory for the meeting. The presence of other participants are non-mandatory. The meeting can proceed in the absence of some of the non-mandatory participants. This allows greater flexibility and more efficient scheduling. This paper introduces the concept of a Quorum in the meeting scheduling process and proposes a two-round negotiating protocol to find the time-slot which meets the quorum requirements. To establish the robustness of our scheduler, we simulated scheduling in our lab, and showed its flexibility in scheduling a meeting.
Today, it is common that enterprises manage several mostly heterogeneous informationsystems to supply their production and business processes with data. There is a need to exchange data between the information system...
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ISBN:
(纸本)9729805067
Today, it is common that enterprises manage several mostly heterogeneous informationsystems to supply their production and business processes with data. There is a need to exchange data between the informationsystems while preserving system autonomy. Hence, an integration approach that relies on a single global enterprise data schema is ruled out. This is also due to the widespread usage of legacy systems. We propose a system, called Propagation Manager, which manages dependencies between data objects stored in different informationsystems. A script specifying complex data transformations and other sophisticated activities, like the execution of external programs, is associated with each dependency. For example, an object update in a source system can trigger data transformations of the given source data for each destination system that depends on the object. Our system is implemented using current XML technologies. We present the architecture and processing model of our system and demonstrate the benefit of our approach by illustrating an extensive example scenario.
This paper presents a novel calculation framework for TTC evaluation with transient stability (TS) constraints with respect to an usual or a critical contingency set. The basic solution strategy for TTC evaluation is ...
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ISBN:
(纸本)9787564112493
This paper presents a novel calculation framework for TTC evaluation with transient stability (TS) constraints with respect to an usual or a critical contingency set. The basic solution strategy for TTC evaluation is introduced, and the whole system architecture and computing flow are given in this paper. In order to implement the security margin of large-scale interconnected power system efficiently and rapidly, especially for on-fine application, a novel distributedparallel computing architecture design philosophy, called as optimal workstation cluster computing model is proposed. Furthermore, some key module design philosophies are issued as well. The proposed distributedparallel computing platform can be easily and conveniently embedded into the existing dynamic security assessment (DSA) system or such systems related to power market to implement the on-line security assessment. On the other hand, the distributedparallel computing platform can make intensive off-line simulation related to the specified case studies.
To find a more effective strategy of managing distributed inventory system under emergency conditions, we combine Vendor Managed Inventory (VMI) with a Hierarchical, distributed, Dynamic, Inventory management (HDDI) s...
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ISBN:
(纸本)9781509028429
To find a more effective strategy of managing distributed inventory system under emergency conditions, we combine Vendor Managed Inventory (VMI) with a Hierarchical, distributed, Dynamic, Inventory management (HDDI) scheme to manage distributed inventory system with decentralized control. Vendor Managed Inventory (VMI) strategy is introduced into a typical distributed inventory system with modified HDDI scheme to increase information sharing of the system. We use system dynamics to simulate the distributed inventory system with VMI and HDDI strategy under emergency conditions. It shows that the distributed inventory system based on VMI and modified HDDI strategy can meet emergency requirements and has lower inventory, compared with traditional inventory system. In addition, a buffer stock mechanism is used in discussed system to balance the contradiction between fill rate and cost under emergency conditions.
Generally, image rendering requires high computing capacity. It is really time consuming to render a movie on a single machine. The use of multiple machines to render a move requires much effort to control the workflo...
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ISBN:
(纸本)9781479989379
Generally, image rendering requires high computing capacity. It is really time consuming to render a movie on a single machine. The use of multiple machines to render a move requires much effort to control the workflow and data. With the emergence of cloud computing, more and more scientists and engineers are moving their tasks from laboratories to public clouds. This migration requires some sort experience on both the cloud architecture and coding in the cloud. This paper proposes a simple service to render movies on Microsoft Azure that accelerates movie rendering. This service, called AzureRender, also introduces task parallelism and cache management to improve performance and reduce cost. A comparative study on image rendering performance and cost between Microsoft Azure and desktop machines is given at the end of the paper.
In this paper we present the architecture of a distributed framework that allows real-time accurate monitoring of large scale high-speed networks. An important component of a large-scale distributed collaboration is t...
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ISBN:
(纸本)9780769534725
In this paper we present the architecture of a distributed framework that allows real-time accurate monitoring of large scale high-speed networks. An important component of a large-scale distributed collaboration is the complex network infrastructure on which it relies. For monitoring and controlling the networking resources an adequate instrument should offer the possibility to collect and store the relevant monitoring information, presenting significant perspectives and synthetic views of how the large distributed system performs. We therefore developed within the MonALISA monitoring framework a system able to collect, store, process and interpret the large volume of status information related to the US LHCNet research network. The system uses flexible mechanisms for data representation, providing access optimization and decision support, being able to present real-time and long-time history information through global or specific views and to take further automated control actions based on them.
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