• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1433-1442
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• 1996

Data distribution of SPMD(Single Program Multiple Data) pattern is one of main features of HPF (High Performance Fortran). This paper describes design is sues for such data distribution and its efficient execution model on TICOM IV computer, named SPAX(Scalable Parallel Architecture computer based on X-bar network). SPAX has a hierarchical clustering structure that uses distributed shared memory(DSM). In such memory structure, it cannot make a full system utilization to apply unanimously either SMDD(shared Memory Data Distribution) or DMDD(Distributed Memory Data Distribution). Here we propose another data distribution model, called DSMDD(Distributed Shared Memory Data Distribution), a data distribution model based on hierarchical masters-slaves scheme. In this model, a remote master and slaves are designated in each node, shared address scheme is used within a node and message passing scheme between nodes. In our simulation, assuming a node size in which system performance degradation is minimized,DSMDD is more effective than SMDD and DMDD. Especially,the larger number of logical processors and the less data dependency between distributed data,the better performace is obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.543-548
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• 2015

Recently, volume of data has been growing dramatically along with the growth of social media and digital devices. However, the existing disk-based distributed file systems have limits to their performance of data processing or data access, due to I/O processing costs and bottlenecks. To solve this problem, the caching technique is being used to manage data in the memory. In this paper, we propose a cache management scheme to handle load balancing in a distributed memory environment. The proposed scheme distributes the data according to the memory size, n distributed environments with different memory sizes. If overloaded nodes occur, it redistributes the the access time of the caching data. In order to show the superiority of the proposed scheme, we compare it with an existing distributed cache management scheme through performance evaluation.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.1-9
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• 2016

Algorithms implementing distributed shared memory (DSM) were developed for ensuring consistency. The performance of DSM algorithms is dependent on system and usage parameters. However, ensuring these algorithms to tolerate faults is a problem that needs to be researched. In this study, we proposed fault-tolerant scheme for DSM system and analyzed reliability and fault-tolerant overhead. Using our analysis, we can choose a proper algorithm for DSM on error prone environment.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.563-570
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• 2006

Distributed control architecture is based on sharing control and data between multiple nodes on a network Communication and task sharing can be distributed between multiple control computers. Although many communication protocols exist, such as TCP/IP and UDP, they do not have the determinism that realtime control demands. Fiber-optic reflective shared memory creates the opportunity for realtime distributed control. This architecture allows control and computational tasks to be divided between multiple systems and operate in a deterministic realtime environment. One such shared memory architecture is based on Curtiss-Wright ScramNET family of fiber-optic reflective memory. MTS has built seismic and structural control software and hardware capable of utilizing ScramNET shared memory, opening up infinite possibilities in research and new capabilities in Hybrid and Model-In-The-Loop control.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.5
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• pp.257-264
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• 2002

In this paper, we give a detailed description of KDSM(KAIST Distributed Shared Memory) system. KDSM is implemented as a user-level library running on Linux 2.2.13, and TCP/IP is used for communication. KDSM uses page-based invalidation protocol, multiple-writer protocol, and supports HLRC(Home-based Lazy Release Consistency) memory consistency model. To evaluate performance of KDSM, we executed 4 scientific applications and compared the result to JLAJLA. The results showed that performance of KDSM almost equal to JIAJIA for 2 applications and performance of KDSM is better than JIAJIA for 2 applications.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.791-802
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• 1996

In this paper, we discuss a distributed shared memory management scheme based on multi-threaded programming model for a large-scale loosely coupled multiprocessor system. The scheme covers three major issues in the distribued shared memory;the address translation table management, the block coherence maintenance, and the block placement policy. The scheme efficiently resolves the general problems occurred in the distributed shared memory such as a false sharing, an unnecessary replication, a block bouncing, and an address aliasing phenomenon. It also provides the application transparency, good scalability, easy implementation, and multithreaded programming model to users.

• Atmosphere
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• v.22 no.1
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• pp.109-115
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• 2012

We parallelized the CFD_NIMR model, which is a numerical meteorological model, for best performance on both of distributed and shared memory parallel computers. This hybrid parallelization uses MPI (Message Passing Interface) to apply horizontal 2-dimensional sub-domain out of the 3-dimensional computing domain for distributed memory system, as well as uses OpenMP (Open Multi-Processing) to apply vertical 1-dimensional sub-domain for utilizing advantage of shared memory structure. We validated the parallel model with the original sequential model, and the parallel CFD_NIMR model shows efficient speedup on the distributed and shared memory system.

• Sleep Medicine and Psychophysiology
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• v.4 no.1
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• pp.15-28
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• 1997

Longterm memory is encoded in the neuronal connectivities of the brain. The most successful models of human memory in their operations are models of distributed and self-organized associative memory, which are founded in the principle of simulaneous convergence in network formation. Memory is not perceived as the qualities inherent in physical objects or events, but as a set of relations previously established in a neural net by simultaneousy occuring experiences. When it is easy to find correlations with existing neural networks through analysis of network structures, memory is automatically encoded in cerebral cortex. However, in the emergence of informations which are complicated to classify and correlated with existing networks, and conflictual with other networks, those informations are sent to the subcortex including hippocampus. Memory is stored in the form of templates distributed across several different cortical regions. The hippocampus provides detailed maps for the conjoint binding and calling up of widely distributed informations. Knowledge about the distribution of correlated networks can transform the existing networks into new one. Then, hippocampus consolidats new formed network. Amygdala may enable the emotions to influence the information processing and memory as well as providing the visceral informations to them. Cortico-striatal-pallido-thalamo-cortical loop also play an important role in memory function with analysis of language and concept. In case of difficulty in processing in spite of parallel process of informations, frontal lobe organizes theses complicated informations of network analysis through temporal processing. With understanding of brain mechanism of memory and information processing, the brain mechanism of mental phenomena including psychopathology can be better explained in terms of neurobiology and meuropsychology.

• ETRI Journal
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• v.20 no.4
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• pp.346-360
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• 1998

It is challenging to parallelize problems with irregular computation and communication. In this paper, we propose an asynchronous algorithm for balancing unpredictable workload on distributed-memory machines. By using an initial workload estimate, we first partition the computations such that the workload is distributed evenly across the processors. In addition, we perform task migrations dynamically for adapting to the evolving workload. To demonstrate the usefulness of our load balancing strategy, we conducted experiments on an IBM SP2 and a Cray T3D. Experimental results show that our task migration strategy can balance unpredictable workload with little overhead. Our code using C and MPI is portable onto other distributed-memory machines.