Earticle

In this paper, a 2-DOF planar parallel manipulator with two revolute actuators and one passive constraining leg. The kinematic analysis of the mechanism is analytically performed : the inverse and forward kinematics problems are solved in closed forms, the workspace is derived systematically, and the three kinds of singular configurations are round. The optimal design to determine the geometric parameters and the operating limits of the actuated legs is performed considering the kinematic manipulability and workspace size. These results of the paper show the effectiveness of the presented manipulator.

This paper presents the kinematics and workspace optimization of the two different 2-DOF (Degrees-of-Freedom) planar parallel mechanisms: one (called 2-RPR mechanism) with translational actuators and the other (called 2-RRR mechanism) with rotational ones. First of all, the inverse kinematics and Jacobian matrix for each mechanism are derived analytically. Then, the workspace including the output-space and the joint-space is systematically analyzed in order to determine the geometric parameters and the operating range of the actuators. Finally, the kinematic optimization of the mechanisms is performed in consideration of their dexterity and rigidity. It is expected that the optimization results can be effectively used as a basic material for the applications of the presented mechanisms to more industrial fields.

양자 컴퓨터의 발전으로 기존 공개키 암호체계의 안전성이 위협받음에 따라 이에 대응할 수 있는 양자내성암호(PQC) 기술 이 주목받고 있다. 본 논문에서는 NIST PQC 표준화의 주요 후보인 ML-KEM 알고리즘을 대상으로 ARM 아키텍처의 NEON 과 RISC-V의 Vector Extension(RVV) 기반 병렬 최적화 구현 동향을 분석하였다. 각 아키텍처의 SIMD 연산 구조와 특성이 ML-KEM의 핵심 연산 최적화에 어떻게 다르게 적용되는지를 유형별로 분석하여 아키텍처별 최적화 전략 프레임워크를 제시 한다. 분석 결과, 고정 길이 SIMD를 사용하는 NEON은 마이크로 아키텍처 수준의 미세 조정이, 가변 길이 벡터를 지원하는 RVV는 알고리즘의 데이터 흐름에 맞는 적응형 최적화가 효과적임을 확인했다. 본 연구는 향후 다양한 환경에서 PQC를 구현 하고 최적화하려는 연구자들에게 실질적인 가이드라인을 제공한다는 점에서 의의를 가진다.

With the advancement of quantum computers, the security of existing public-key cryptosystems is being threatened, leading to increased attention on quantum-resistant cryptography (PQC) technologies that can address this issue. This paper analyzes the trends in parallel optimization implementations of the ML-KEM algorithm, a major candidate for NIST PQC standardization, based on the NEON of the ARM architecture and the Vector Extension (RVV) of RISC-V. We categorize and analyze how the distinct SIMD characteristics of each architecture are differently applied to optimize ML-KEM's core operations. Based on this synthesis, we present an architectural optimization strategy framework. The analysis confirms that NEON, with its fixed-length SIMD, benefits from microarchitectural fine-tuning, while RVV, supporting variable-length vectors, is effective with adaptive optimizations tailored to algorithmic data flow. This study is significant in that it provides a practical guideline for researchers implementing and optimizing PQC on diverse hardware platforms.

본 논문에서는 GPU 병렬 처리 하드웨어 아키텍처 내 최소 물리적 스레드 실행 단위(warp) 내에서 shifted sort 기반 k개 최근접 이웃 검색 기법을 구현하는 방법을 논의하고 일반적으로 동일한 목적으로 널리 사용되는 GPU 기반 kd-tree 및 CPU 기반 ANN 라이브러리와 비교한 결과를 제시한다. 또한 많은 애플리케이션에서 k가 비교적 작은 값이 필요한 경우가 많다는 사실을 고려해서 k가 warp 내부에서 직접 처리 가능한 2, 4, 8, 16개일 때 최적화에 집중한다. 구현 세부에서는 사용한 CUB 공개 라이브러리의 루프 내 메모리 관리 방법, GPU 하드웨어 직접 명령 적용 방법 등의 최적화 방법을 논의한다. 실험 결과, 제안하는 방법은 기존의 GPU 기반 유사 방법에 비해 데이터 지점과 질의 지점의 개수가 각각 $2^{23}$개 일 때 16배 이상의 빠른 처리 속도를 보였으며 이러한 경향은 처리해야 할 데이터의 크기가 커지면 더욱 더 커지는 것으로 판단된다.

This paper presents and discusses an implementation of the GPU shifted sorting method to find approximate k nearest neighbors which executes within "warp", the minimum execution unit in GPU parallel architecture. Also, this paper presents the comparison results with other two common nearest neighbor searching methods, GPU-based kd-tree and ANN (Approximate Nearest Neighbor) library. The proposed implementation focuses on the cases when k is small, i.e. 2, 4, 8, and 16, which are handled efficiently within warp to consider it is very common for applications to handle small k's. Also, this paper discusses optimization ways to implementation by improving memory management in a loop for the CUB open library and adopting CUDA commands which are supported by GPU hardware. The proposed implementation shows more than 16-fold speed-up against GPU-based other methods in the tests, implying that the improvement would become higher for more larger input data.

최근 빅데이터 이슈가 화두가 됨에 따라 대학, 산업체, 연구소 등에서는 다양한 데이터들을 수집, 분석 하려는 노력이 활성화 되고 있다. 여기에는 과거부터 축적된 데이터, 현재에 바로 분석이 불가능하더라도 잠재적인 의미를 가지고 있는 데이터 등 대량의 데이터들이 수집되어 의미론적인 분석을 통해 가치 있는 분석결과를 얻게 된다. 이를 위해 전 세계적으로 대용량의 데이터 요구를 처리 할 수 있는 고성능 스토리지 시스템의 수요가 증가하고 있다. 또한, 여러 사용자들에게 축적된 대량의 데이터에 동시에 접속하여 다양한 분석을 수행할 수 있도록 안정성 있는 병렬 분산파일시스템을 제공해야 한다. 본 연구에서는 위와 같이 안정성 있는 파일시스템을 제공하기 위해 반드시 고려되어야 할 스토리지 시스템의 I/O 대역폭, 메타데이터의 성능 등을 파악하고 최적의 환경을 구성하기 위한 방법을 제시하고자 한다.

Recently, Big Data issue has become a buzzword and universities, industries and research institutes have been efforts to collect, analyze various data enabled. These things includes accumulated data from the past, even if it is not possible to analysis at this present immediately a which has the potential means. And we are obtained a valuable result from the collected a large amount of data via the semantic analysis. The demand for high-performance storage system that can handle large amounts of data required is increasing around the world. In addition, it must provide a distributed parallel file system that stability to multiple users too perform a variety of analyzes at the same time by connecting a large amount of the accumulated data In this study, we identify the I/O bandwidth of the storage system to be considered, and performance of the metadata in order to provide a file system in stability and propose a method for configuring the optimal environment.

To improve the performance of BLAS 2 GEMV subroutine under the latest instruction set, Intel AVX, this paper presents a new approach to analyze the new generation instruction set and enhance the efficiency of current data-oriented math subroutines. The whole optimizing process involves memory access optimization, SIMD optimization and parallel optimization. Also, this paper shows the comparison between the traditional SSE instruction set and the AVX instruction set. Experiments show that the optimized GEMV function has obtained considerable increase on performance. Compared with the Intel MKL, GotoBLAS, ATLAS, this optimized GEMV exceeds these BLAS implementations from 5% to 10%.

New performance leaps has been achieved with multiprogramming and multi-core systems. Present parallel programming techniques and environment needs significant changes in programs to accomplish parallelism and also constitute complex, confusing and error-prone constructs and rules. Intel Cilk Plus is a C based computing system that presents a straight forward and well-structured model for the development, verification and analysis of multi-core and parallel programming. In this article, two programs are developed using Intel Cilk Plus. Two sequential sorting programs in C/C++ language are converted to multi-core programs in Intel Cilk Plus framework to achieve parallelism and better performance. Converted program in Cilk Plus is then checked for various conditions using tools of Cilk and after that, comparison of performance and speedup achieved over the single-core sequential program is discussed and reported.

The focus of this research is on the development, modeling and high precision robust control of an electro-mechanical continuum robot manipulator that serves as a sensing and motion system for hybrid testing. In this research parallel fuzzy logic theory is used to compensate the system dynamic uncertainty controller based on sliding mode theory. This design resulted in strongly non-linear and coupled dynamics as well as an inertial moving platform that attracted model-based control strategies. A novel non-linear control technique based on sliding mode Lyapunov based was selected to meet the multiple simultaneous specification control of nonlinear, uncertain and asymptotic tracking. Sliding mode controller (SMC) is a significant nonlinear controller under condition of partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for continuum robot manipulator, because this controller is robust and stable in presence of partly uncertainties. Sliding mode controller was used to achieve a stable tracking, while the parallel fuzzy-logic optimization added intelligence to the control system through an automatic tuning of the sliding mode methodology uncertainties. Simulation results demonstrated the validity of the Mamdani parallel fuzzy-optimization control with asymptotic and stable tracking at different position inputs. This compensation demonstrated a well synchronized control signal at different excitation conditions.

This research contributes to the on-going research effort by exploring alternate methods for soft computing optimization the highly nonlinear and uncertain systems. This research addresses two basic issues related to the control of an uncertain system; (1) design of a robust feedback controller, and (2) the design of a parallel artificial intelligence based optimization to increase the result qualification. The robust backstepping controller proposed in this research is used to further demonstrate the appealing features exhibited by the continuum robot. Robust feedback controller is used to position control of continuum robot in presence of uncertainties. Using Lyapunov type stability arguments, a robust backstepping controller is designed to achieve this objective. The controller developed in this research is designed in two steps. Firstly, a robust stabilizing torque is designed for the nominal continuum robot dynamics derived using the constrained Lagrangian formulation. Next, the fuzzy logic methodology applied to it to solution uncertainty problem by parallel optimization. The fuzzy model free optimization is formulated to minimize the problem of nonlinear formulation of uncertain systems.

도로이동 오염원 대기환경 빅데이터는 상시 교통량 조사장비인 AVC, VDS, WIM, DTG를 활용한 차종, 속도, 하중 등 실시간 교통류 데이터와 GIS를 활용한 도로형상(오르막, 내리막, 회전구간) 데이터를 연계한 교통류 데이터로 구성되어 있다. 또한, 일반적인 데이터와 달리 단위시간 당 데이터가 많이 발생하고, 다양한 포맷을 가지고 있다. 특히, 이들 상세 교통류 정보로 수집되는 대용량의 실시간 데이터들은 약 총 740만 건/시간 이상이 수집되어 저장 및 가공되 기 때문에 효율적으로 데이터를 처리할 수 있는 시스템이 필요하다. 따라서 본 연구에서는 도로이동 오염뭔 대기환경 빅데이터 시각화를 위한 오픈소스 기반의 데이터 병렬처리 성능 최적화 연구를 수행한다.

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

This paper discusses an effective synchronization algorithm. It is different from the existing synchronization methods by inserting appropriate synchronization instructions between statements according to different kinds of data dependences. The overhead caused by too many synchronization instructions in a loop can be a critical problem. Synchronization optimization is a method which discriminates and eliminates the redundant synchronization instructions in a loop. In this paper, a new synchronization optimization algorithm - ICPG (Improved Controlled Path Graph) - is developed, and the algorithm is extended to the case of nested loops. In case of nested loops, the existing methods were not safe because of the incomplete management in hyper-rectangle areas, etc. But, the errorneous methods are completely corrected in this paper. Finally, performance analysis using simulation on the UNIX operating system is carried out. It is shown that the ICPG algorithm is much more effective than the existing methods.

A three-dimensional aerodynamic shape optimization technique in inviscid compressible flows is developed by using a parallel continuous adjoint formulation on unstructured meshes. A new surface mesh modification method is proposed to overcome difficulties related to patch-level remeshing for unstructured meshes, and the effect of design sections on aerodynamic shape optimization is examined. Applications are made to three-dimensional wave drag minimization problems including an ONERA M6 wing and the EGLIN wing-pylon-store configuration. The results show that the present method is robust and highly efficient for the shape optimization of aerodynamic configurations, independent of the number of design variables used.

A nonsmooth PGD scheme for minimizing a nonsmooth convex function is presented. In the parallelization step of the algorithm, a method due to Pang, Han and Pangaraj (1991), [7], is employed to solve a subproblem for constructing search directions. The convergence analysis is given as well.

In practical designs, most of the multidisciplinary problems have a large-size and complicate design system. Since multidisciplinary problems have hundreds of analyses and thousands of variables, the grouping of analyses and the order of the analyses in the group affect the speed of the total design cycle. Therefore, it is very important to reorder and regroup the original design processes in order to minimize the total computational cost by decomposing large multidisciplinary problems into several multidisciplinary analysis subsystems (MDASS) and by processing them in parallel. In this study, a new decomposition method is proposed for parallel processing of multidisciplinary design optimization, such as collaborative optimization (CO) and individual discipline feasible (IDF) method. Numerical results for two example problems are presented to show the feasibility of the proposed method.

We are under development of a 3D PET scanner with depth of interaction (DOI) capable of high sensitivity and high resolution. In this scanner, a maximum data transfer rate of coincidence pair's event information is 10 Mcps and one event is a 64-bit data format. This maximum data transfer rate corresponds by 10 times a conventional PET scanner. A data acquisition system, which fulfills the specification of this scanner, is considered for parallel collection with banks including several coincidence units. Data transfer rate is improved by optimizing parameters of a message size, and so on.

축류 팬(axial fan)은 팬이 회전하면서 작은 압력 상승을 만들어 다량의 공기를 불어주는 유체 기계로써 최근 축류 팬의 소음 저감이 중요하게 인식되고 있다. 본 연구는 팬 주위의 유동 소음을 해석하는 MPI 병렬프로그램 방법 및 최적화 기법에 대해 다룬다. 이때 수억 개 이상의 격자에서 수만 포인트의 소음원을 해석하기 위해서 2차원 도메인 분할 방법을 사용해서 MPI 병렬화를 하였다. 이때 대규모 계산 시 MPI 프로세스 간의 통신이 많이 발생하여 성능이 심각하게 느려지는 현상이 발생한다. 이를 극복하기 위해 MPI 일방향 통신을 적용하였다. 뿐만 아니라 통신 및 메모리 최적화 방법을 통해 최대 2.97배 향상시켰다. 마지막으로 KISTI 타키온2 슈퍼컴퓨터를 활용하여 전체 시뮬레이션 실험에서 유동 계산 시 6,144코어에서 최대 12배, 소음 계산 시 128코어에서 최대 6배의 성능향상을 달성하였다.

Recently, noise reduction in an axial fan producing the small pressure rise and large flow rate, which is one type of turbomachine, is recognized as essential. This study describes the design and optimization techniques of MPI parallel program to simulate the flow-induced noise in the axial fan. In order to simulate the code using 100 million number of grids for flow and 70,000 points for noise sources, we parallelize it using the 2D domain decomposition. However, when it is involved many computing cores, it is getting slower because of MPI communication overhead among nodes, especially for the noise simulation. Thus, it is adopted the one-sided communication to reduce the overhead of MPI communication. Moreover, the allocated memory and communication between cores are optimized, thereby improving 2.97x compared to the original one. Finally, it is achieved 12x and 6x faster using 6,144 and 128 computing cores of KISTI Tachyon2 than using 256 and 16 computing cores for the flow and noise simulations, respectively.