• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.330-334
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• 2004

Java bytecode is stack-base code. Stack-base code makes analysis and optimization hardly because use stack access imperative. Therefore, fragment of code that is problem that occur in stack-base code optimization, loss of type information, unnecessary Load and Store can appear. Optimization and analysis of bytecode design bytecode framework by solution way of problem that is difficult. This paper indicates optimization of bytecode and hangup of analysis, and describe research contents about existent byte code optimization technology. This propose byte code framework by the alternative to simplify analysis and optimization of byte code.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.450-454
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• 2015

Short execution time is the major performance factor for computer systems. This performance factor is directly determined by code quality, which is influenced by the compiler's optimizations. However, a compiler has limitations when optimizing source code due to insufficient information. Thus, if programmers can learn the reasons why a compiler fails to apply optimizations, they can rewrite code that is more easily understood by the compiler, and thus improve performance. In this paper, we propose a compiler that provides a programmer with reasons for failed optimization and recognizes programmer's additional information to obtain better optimization. As a result, we obtain performance improvement, i.e., reducing execution time and code size, by taking advantage of additional optimization opportunities.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.31-38
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• 2007

Code Optimization is converting to a code that is equivalent to given program but more efficient, and this process is processed in Code Optimizer. This paper designed and processed Code Optimizer Generator that automatically generates Code Optimizer. In other words Code Optimizer is automatically generated for DFA Pattern Matching which finds the optimal code for the incoming pattern description. DFA Pattern Matching removes redundancy comparisons that occur when patterns are sought for through normalization process and improves simplification and structure of pattern shapes for low cost. Automatic generation of Code Optimization for DFA Pattern Matching eliminates extra effort to generate Code Optimizer every time the code undergoes various transformations, and enables formalism of Code Optimization. Also, the advantage of making DFA for optimization is that it is faster and saves cost of Code Optimizer Generator.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.112-121
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• 2013

An approach for composing a performance optimized computational code is suggested for the latest microprocessors. The concept of the code optimization, termed localization, is maximizing the utilization of the second level cache that is common to all the latest computer systems, and minimizing the access to system main memory. In this study, the localized optimization of the LU-SGS (Lower-Upper Symmetric Gauss-Seidel) code for the solution of fluid dynamic equations was carried out in three different levels and tested for several different microprocessor architectures widely used these days. The test results of localized optimization showed a remarkable performance gain of more than two times faster solution than the baseline algorithm for producing exactly the same solution on the same computer system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.37-42
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• 1997

Off-line feed rate scheduling is an advanced methodology to automatically determine optimum feed rates for the optimization of NC code. However, the present feed rate scheduling systems have lim~tations to generate the optimized NC codes because they use the material removal rate or non-generalized cutting force model. In this paper, a feed rate scheduling system based on an improved cutting force model that can predrct cutting forces exactly in general machining was presented. Original blocks of NC code were divided to small ones with the modified feed rates to adjust the peak value of cutting forces to a constant vale. The characteristic of acceleration and deceleration for a given machrne tool was considered when off-line feed rate scheduhng was performed. Software for the NC code optimization was developed and applied to pocket machining simulation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.04a
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• pp.187-194
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• 1995

Traditional genetic algorithms(GA) have mostly used binary code for representing design variable. The binary code GA has many difficulties to solve optimization problems with continuous design variables because of its targe computer core memory size, inefficiency of its computing time, and its bad performance on local search. In this paper, a real code GA is proposed for dealing with the above problems. So, new crossover and mutation processes of read code GA are developed to use continuous design variables directly. The results of real code GA are compared with those of binary code GA for several single and multiple objective optimization problems. As results of comparisons, it is found that the performance of the real code GA is better than that of the binary code GA, and concluded that the rent code GA developed here can be used for the general optimization problem.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1079-1088
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• 2004

Generally, the code motion algorithm accomplishes the run-time optimal connected with the computational optimifation and the register overhead This paper proposes a sparse code motion, which considers the code size, in addition to computational optimization and lifetime optimization. The BCM algorithm carries out the optimal code motion computationally and the LCM algorithm reduces the register overhead in a sparse code motion algorithm. A sparse code motion algorithm is optimum algorithm computationally and lifetime because of suppression unnecessary code motion This algorithm improves runtime and efficiency of the program than the previous work through the performance test.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.124-133
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• 2022

With the development of hardware technology and the advancement of numerical model methods, more precise weather forecasts can be carried out. In this paper, we propose a Unicon Optimization scheme combining Loop Vectorization, Dependency Vectorization, and Code Modernization to optimize and increase Maintainability the Unicon source contained in SCAM, a simplified version of CESM, and present an overall SCAM structure. This paper tested the unicorn optimization scheme in the SCAM structure, and compared to the existing source code, the loop vectorization resulted in a performance improvement of 3.086% and the dependency vectorization of 0.4572%. And in the case of Unicorn Optimization, which applied all of these, the performance improvement was 3.457% compared to the existing source code. This proves that the Unicorn Optimization technique proposed in this paper provides excellent performance.

• Journal of Korea Multimedia Society
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• v.10 no.5
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• pp.687-697
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• 2007

Although the Java bytecode has numerous advantages, there are also shortcomings such as slow execution speed and difficulty in analysis. Therefore, in order for the Java class file to be effectively executed under the execution environment such as the network, it is necessary to convert it into optimized code. We implemented CTOC for transforming to optimized code. In Optimization, SSA Form that distinguish variable by assignment is used to determine value and type statically. Copy propagation, dead code elimination optimization is applied to SSA Form. However, existing SSA Form is related to variable than expression. Therefore, in this paper, to performing optimization to SSA Form expression, after performing copy propagation and dead code elimination, in addition to that, partial redundant expression elimination is performed

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.51-58
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• 2004

Optimization of engine desist and operation parameters using a genetic algorithm was demonstrated for direct injection diesel engine combustion. A micro genetic algorithm and a modified KIVA-3V code were used for the analysis and optimization of the engine combustion. At each generation of the optimization step the micro genetic algorithm generated five groups of parameter sets, and the five cases of KIVA-3V analysis were to be performed either in series or in parallel. The micro genetic algorithm code was also parallelized by using MPI programming, and a multi-CPU parallel supercomputer was used to speed up the optimization process by four times. An example case for a fixed engine speed was performed with six parameters of intake swirl ratio, compression ratio, fuel injection included angle, injector hole number, SOI, and injection duration. A simultaneous optimization technique for the whole range of engine speeds would be suggested for further studies.