• Nuclear Engineering and Technology
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• v.30 no.4
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• pp.298-307
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• 1998

In order to design mutual communication between a distributed control system and a function test facility, we used the Inter-Process Communication(IPC) in two systems and Transmission Control Protocol/Internet Protocol(TCP/IP) protocol. The data from the function test facility are put in the shared memory using an IPC, which is then accessed by the distributed control system through an Application Program Interface(API). The server in the function test facility includes two processes(one for sending and one for receiving), which are generated by the fork function from the client signal. The client in the distributed control system includes two separate programs(one for receiving and one for sending).

• Smart Media Journal
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• v.4 no.3
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• pp.16-23
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• 2015

As the IT technology advances, data processing system is required to handle and process large amounts of data. However, the existing On-Disk system has limit to process data which increase rapidly. For that reason, the In-Memory system is being used which saves and manages data on the fast memory not saving data into hard disk. Although it has fast processing capability, it is necessary to use the fault tolerance techniques in the In-Memory system because it has a risk of data loss due to volatility which is one of the memory characteristics. These fault tolerance techniques lead to performance degradation of In-Memory system. In this paper, we classify the data into Hot and Cold data in consideration of the data usage characteristics in the In-Memory system and propose compound backup technique to ensure data persistence. The proposed technique increases the persistence and improves performance degradation.

• 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.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.291-298
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• 2006

A parallelized topology design optimization method is developed on a distributed memory system. The parallelization is based on a domain decomposition method and a boundary communication scheme. For the finite element analysis of structural responses and design sensitivities, the PCG method based on a Krylov iterative scheme is employed. Also a parallelized optimization method of optimality criteria is used to solve large-scale topology optimization problems. Through several numerical examples, the developed method shows efficient and acceptable topology optimization results for the large-scale problems.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.107-117
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• 1996

This paper proposes a conceptual model for distributed problem solving(DPS), where cooperation and communication among agents are based on virtual shared memory (VSM) In this model, all agents in a DPS system view all the memory in a distributed computer system as a single shared memory in which data, tasks, and results can in a distributed computer system as a single shared memory, in which data, tasks, and results can / be accessed by any of the agents. Several agents cooperatively solve a complex problem, as agents write data, intermediate results of execution, and tasks requested to other agents to VSM and other agents read or execute them. Also, in order to develop DPS systems based on the proposed conceptual model, this paper designs a DPS system development environment(DPS-VSM)using Network Linda. Thi spaper shows utility ofthe proposed model by presenting an example of simulation a VSM-based DPS system, and analyzes the model by comparing the features of DPS- VSM with some other DAI programming shells.

• Journal of KIISE
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• v.42 no.9
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• pp.1109-1116
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• 2015

In this paper, we propose a query processing approach that uses the Spark functional programming and distributed memory system to solve the computational overhead of SPARQL. In the semantic web, RDF ontology data is produced at large scale, and the main challenge for the semantic web is to query and manipulate such a large ontology with a high throughput. The most existing studies on SPARQL have focused on deploying the Hadoop MapReduce framework, and although approaches based on Hadoop MapReduce have shown promising results, they achieve a low level of throughput due to the underlying distributed file processes. Therefore, in order to speed up the query processes, we suggest query- processing methods that are based on memory caching in distributed memory system. Our approach is also integrated with a clause unification method for propagating between the clauses that exploits Spark join, map and filter methods along with caching. In our experiments, we have achieved a high level of performance relative to other approaches. In particular, our performance was nearly similar to that of Sempala, which has been considered to be the fastest query processing system.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.7_8
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• pp.331-340
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• 2003

Low-cost commodity SMP(Symmetric Multiprocessor) is widely used as a node of cluster system. In this paper, we implement and evaluate the performance of SDSM system for SMP clusters. Our SDSM system provides HLRC(Home-based Lazy Release Consistency) memory consistency model. Our protocol utilize shared memory within same SMP node, so that page fetch and message passing through network can be reduced. It is implemented on 8 node of 2-way Pentium-III SMP interconnected with 100Mbps Fast Ethernet, and uses TCP/IP for transport/network layer protocol. The experiment with eight applications shows that our SMP protocol achieves maximum 33% speedup improvement and 13%-52% reduction of page fetch compared with uniprocessor protocol.

• International Journal of Contents
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• v.12 no.1
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• pp.60-64
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• 2016

As new applications of cloud data management system (CDMS) such as online games, cooperation edit, social network, and so on, are increasing, transaction processing capabilities for CDMS are required. Several transaction processing methods for cloud data management system (CDMS) have been proposed. However, existing transaction processing methods have some problems. Some of them provide limited transaction processing capabilities. Some of them are hard to be integrated with existing CDMSs. In this paper, we proposed a new concurrency control method to support transaction processing capability for CDMS to solve these problems. The proposed method was designed and implemented based on Spark, an in-memory distributed processing framework. It uses RDD (Resilient Distributed Dataset) model to provide fault tolerant to data in the main memory. In our proposed method, database stored in CDMS is loaded to main memory managed by Spark. The loaded data set is then transformed to RDD. In addition, we proposed a multi-version concurrency control method through immutable characteristics of RDD. Finally, we performed experiments to show the feasibility of the proposed method.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.1098-1105
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• 1999

The caches in distributed shared memory systems enhance the performance by reducing memory access latency and communication overhead, but they must solve the cache coherence problem. This paper proposes a new directory protocol to solve the cache coherence problem and to improve the system performance in distributed shared memory systems. To maintain the cache coherence of shared data, processors within a limited distance reduce the communication overhead by using a bit-vector like the full directory scheme. Processors over a limited distance store pointers in a directory pool. Since the bit-vector and the directory pool remove the unnecessary cache invalidations, the proposed scheme reduces the communication traffic and improves the system performance. The dynamic limited directory scheme reduces the communication traffic up to 66 percents compared with the limited directory scheme and the number of directory access up to 27 percents compared with the dynamic pointer allocation scheme.