• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.575-582
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• 2000

Because FIFO thread scheduling used in the existing multithreaded models does not consider locality in programs, it may result in the decrease of the performance of execution, caused by the frequent context switching overhead and delay of execution of relatively short frames. Quantum unit scheduling enhances the performance a little, but it still has the problems such as the decrease in the processor utilization and the longer delay due to its heavy dependency on the priority of the quantum units. In this paper, we propose shortest-frame-first(SFF) thread scheduling algorithm. Our algorithm selects and schedules the frame that is expected to take the shortest execution time using thread size and synchronization information analyzed at compile-time. We can estimate the relative execution time of each frame at compile-time. Using SFF thread scheduling algorithm on the multithreaded models, we can expect the faster execution, better utilization of the processor, increased throughput and short waiting time compared to FIFO scheduling.

• Journal of Computing Science and Engineering
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• v.5 no.2
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• pp.111-120
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• 2011

Data mining algorithms should exploit new hardware technologies to accelerate computations. Such goal is difficult to achieve in database management system (DBMS) due to its complex internal subsystems and because data mining numeric computations of large data sets are difficult to optimize. This paper explores taking advantage of existing multithreaded capabilities of multicore CPUs as well as caching in RAM memory to efficiently compute summaries of a large data set, a fundamental data mining problem. We introduce parallel algorithms working on multiple threads, which overcome the row aggregation processing bottleneck of accessing secondary storage, while maintaining linear time complexity with respect to data set size. Our proposal is based on a combination of table scans and parallel multithreaded processing among multiple cores in the CPU. We introduce several database-style and hardware-level optimizations: caching row blocks of the input table, managing available RAM memory, interleaving I/O and CPU processing, as well as tuning the number of working threads. We experimentally benchmark our algorithms with large data sets on a DBMS running on a computer with a multicore CPU. We show that our algorithms outperform existing DBMS mechanisms in computing aggregations of multidimensional data summaries, especially as dimensionality grows. Furthermore, we show that local memory allocation (RAM block size) does not have a significant impact when the thread management algorithm distributes the workload among a fixed number of threads. Our proposal is unique in the sense that we do not modify or require access to the DBMS source code, but instead, we extend the DBMS with analytic functionality by developing User-Defined Functions.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.826-836
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• 2002

We need an enormous amount of memories for name spaces as well as additional processors if we are to effectively exploit a massively parallelism in nested loops of functional languages such as Id. If there is no sufficient amount of memories enough to exploit that parallelism, the execution of programs can be aborted during the unfolding of loops. Additionally, if loops are overunfolded, compared with the number of processors available, the system performance can be degraded severely due to the overhead of loop unfolding. This paper suggests and analyzes an algorithm which can be used to effectively unfold nested loops of functional languages on multithreaded architectures. This algorithm has a feature to unfold a given nested loop safely and near optimally, considering the system resources of processors and memories available when the loop is to be unfolded.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.75-83
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• 2007

Multithreaded model is an effective parallel system in that it can reduce the long memory reference latency time and solve the synchronization problems. When compiling the non-strict functional programs for the multithreaded parallel machine, the most important thing is to find an set of sequentially executable instructions and to partitions them into threads. The existing partitioning algorithm partitions the condition of conditional expression, true expression and false expression into the basic blocks and apply local partitioning to these basic blocks. We can do the better partitioning if we modify the definition of the thread and allow the branching within the thread. The branching within the thread do not reduce the parallelism, do not increase the number of synchronization and do not violate the basic rule of the thread partitioning. On the contrary, it can lengthen the thread and reduce the number of synchronization. In the paper, we enhance the method of the partition of threads by combining the three basic blocks into one of two blocks.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.12
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• pp.655-664
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• 2002

In many data-parallel applications massive parallelism can be easily extracted through data distribution. But it often causes very long communication latency. This paper shows that task parallelism, which is extracted from data-parallel programs, can be exploited to hide such communication latency Unlike the most previous researches over exploitation of task parallelism which has not been considered together with data parallelism, this paper describes exploitation of task parallelism in the context of data parallelism. PCFG(Parallel Control Flow Graph) is proposed to represent a multithreaded program consisting of a few task threads each of which can include a few data-parallel loops. It is also described how a PCFG is constructed from a source data-parallel program through HDG(Hierarchical Dependence Graph) and how the multithreaded program can be constructed from the PCFG.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.148-155
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• 2002

Multithreaded models improve the efficiency of parallel systems by combining inner parallelism, asynchronous data availability and the locality of von Neumann model. This model executes thread code which is generated by compiler and of which quality is given by the method of generation. But multithreaded models have the demerit that execution model is restricted to a specific platform. On the contrary, Java has the platform independency, so if we can translate from threads code to Java bytecode, we can use the advantages of multithreaded models in many platforms. Java executes Java bytecode which is intermediate language format for Java virtual machine. Java bytecode plays a role of an intermediate language in translator and Java virtual machine work as back-end in translator. But, Java bytecode which is translated from multithreaded models have the demerit that it is not secure. This paper, multhithread code whose feature of platform independent can execute in java virtual machine. We design and implement translator which translate from thread code of multithreaded code to Java bytecode and which check secure problems from Java bytecode.

• ETRI Journal
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• v.39 no.1
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• pp.124-134
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• 2017

Data races are one of the most difficult types of bugs in concurrent multithreaded systems. It requires significant time and cost to accurately detect bugs in complex large-scale programs. Although many race detection techniques have been proposed by various researchers, none of them are effective in all aspects. In this paper, we compare the performance of five recent dynamic race detection techniques: FastTrack, Acculock, Multilock-HB, SimpleLock+, and causally precedes (CP) detection. We experimentally demonstrate the strengths and weaknesses of these dynamic race detection techniques in terms of their detection capability, running time, and runtime overhead using 20 benchmark programs with different characteristics. The comparison results show that the detection capability of CP detection does not differ from that of FastTrack, and that SimpleLock+ generates the lowest overhead among the hybrid detection techniques (Acculock, SimpleLock+, and Multilock-HB) for all benchmark programs. SimpleLock+ is 1.2 times slower than FastTrack on average, but misses one true data race reported from Mutilock-HB on the large-scale benchmark programs.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.708-718
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• 1999

본 논문에서 제안하는 시스템은 일반적인 병렬 시스템의 하드웨어 구조에서, 다중 스레드 계산 모델을 이용하여 객체 지향 프로그래밍 환경을 구현한 시스템이다. 제안하는 시스템을 효과적으로 구현하기 위하여 컴파일러와 실행 시간 시스템의 측면에서 여러 가지 기법을 제시한다. 컴파일러의 측면에서는 멤버 변수의 접근 분석, 메소드의 병렬성 분석 기법을 제시하고, 실행 시간 시스템에서는 실시간 스레드/메시지 결합, 프레임 공유 기법을 제시한다. 본 논문에서 제안된 프로그래밍 환경은, MPI 메시지 인터페이스를 이용하여 구현하였으며, 벤치마크 프로그램을 실행함으로써 성능 분석을 하였다. 분석의 결과는 실행시간 시스템의 여러 가지 기법들이 성능 향상에 많은 효과가 있음을 보여주며, 이러한 결과는 일반적인 병렬 시스템에서도 적용 가능하다.Abstract In this paper, we suggest an object-oriented programming environment with multithreaded computation model on general parallel processing systems. We developed many methods for our environment to be efficient : in compiler, the analysis of member variable and method parallelism, and in runtime system, thread/message merging and frame sharing. The programming environment is implemented with MPI message interface, and its performance is analyzed with executing benchmark programs. The results show that the developed methods have influence on performance improvement, and this improvement can be applied to general parallel processing systems.

• Information and Communications Magazine
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• v.19 no.11
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• pp.70-84
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• 2002

In this paper we discuss a multi-threaded baseband Processor capable of executing all physical layer processing of high data rate communications systems completely in software. We discuss the enabling technology for a software defined radio approach and present results for GPRS. 802.11b, and 2Mbps WCDMA. All of these protocols can be executed in real-time on the SB9600 chip using the Sandblaster core.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.73-75
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• 2001

본 논문에서는 다중 스레드 Java 프로그램의 실행 중 처리되지 않는 예외상황을 실행 전에 미리 예측하는 분석 방법을 제안한다. Java에서는 안전성 문제 때문에 다중 스레드 사이에서 예외 상황을 발생시키지 않도록 제한하고 있는데 반해, 본 연구에서는 프로그래머가 자유롭게 다중 스레드 사이에 예외상황을 발생시킬 수 있도록 언어를 확장한 후에 그 프로그램에서 처리되지 않는 예외상황을 예측해낸다. 이 분석 방법은 다중 스레드 Java 프로그램의 각 스레드에서 동시에 수행될 수 있는 부분들을 미리 예측해내고, 이 분석 정보를 이용하여 다중 스레드 사이에서 예외상황을 발생시킬 때 처리되지 않는 예외상황을 예측한다.