서버와 모바일 환경에서의 인공 신경망 다중 추론 기법

학위논문(박사) -- 서울대학교대학원 : 공과대학 컴퓨터공학부, 2022. 8. 전병곤.The development of deep learning algorithms and innovative hardware advancements facilitates use cases in which multiple DNNs are processed at once. Among the many instances of multi-DNN computation, we focus on two categories in this disseration: mobile applications that utilize several DNNs to solve complex tasks such as extended reality applications, and server-side setups in which multiple DNNs are served within the same pool of GPU resources. For mobile environments, we propose Band, a new mobile inference system that coordinates multi-DNN workloads on heterogeneous processors. Band examines a DNN and partitions it into a set of subgraphs, while taking operator dependency into account. At runtime, Band dynamically selects a schedule of subgraphs from multiple possible schedules, following the scheduling goal of a pluggable scheduling policy. Fallback operators, which are not supported by certain mobile processors, are also considered when generating subgraphs. For server environments, we propose NetFuse, a framework that merges multiple DNN models who share the same architecture but have different weights and different inputs. NetFuse is made possible by replacing operations with more general counterparts that allow a set of weights to be associated with only a certain set of inputs.딥 러닝 알고리즘의 발전과 관련 하드웨어에서의 기술 혁신에 힘입어, 한 번에 여러 개의 DNN(인공 신경망)에 대한 처리를 필요로 하는 사례들이 생기고 있다. 이러한 다중 DNN 처리 사례들 중에서, 이 학위논문에서는 두 범주의 사례들에 집중하고 자 한다. 첫 번째 범주는 여러 DNN을 사용하여 확장 현실 응용과 같은 복잡한 작업을 필요로 하는 모바일 기기 응용 사례들이고, 두 번째 범주는 서버 환경에서 주어진 GPU 자원을 활용하여 많은 수의 DNN을 처리해야 하는 사례들이다. 본 논문에서는 먼저 Band라는 모바일 추론 시스템을 소개한다. Band는 모바일 기기의 이기종 프로세서들을 활용하여 다중 DNN 처리 작업을 효율적으로 스케줄링한다. 이 시스템은 DNN들을 수행하기에 앞서 이들을 분석하여, 연산 간 종속 관계를 유치한 채 하나의 DNN을 여러 개의 서브그래프로 분할한다. 그 후 런타임 상황에서는, 사전에 설정 가능한 스케줄링 정책을 따라 DNN을 수행하기 위한 서브그래프의 묶음을 여러 가능한 스케줄 중에서 동적으로 선택한다. 또한 이 과정에서, 특정 프로세서들에서는 수행이 불가능한 Fallback 연산도 고려하여 서브그래프를 형성하게 된다. 다음으로는 서버 환경을 대상으로 하는 다중 DNN 추론 시스템 NetFuse를 제안한다. NetFuse는 연산 구조가 같지만 입력과 파라미터가 다른 여러 DNN 들을 병합하여 수행하는 프레임워크다. NetFuse에서는 DNN의 각 연산을 더 일반적인 형태의 연산으로 치환하여, 입력의 특정 값들이 파라미터의 특정 값들과만 연결되도록 함으로써 DNN 병합을 가능하게 만든다.Abstract i 1 Introduction 1 2 Background and Related Work 4 2.1 Multi-DNN Mobile Applications 4 2.1.1 Workload Characteristics 5 2.2 Multi-DNN Use Cases at the Server 8 2.3 Related Work 10 3 Band: Multi-DNN Inference on Mobiles 13 3.1 Motivation 13 3.1.1 Utilizing Heterogeneous Processors 13 3.1.2 Challenges in Coordination 15 3.2 Band: Subgraph-Centric Coordination 21 3.2.1 System Overview 22 3.2.2 Subgraph Partitioning 24 3.2.3 Subgraph Scheduling 27 3.3 Implementation 33 3.3.1 Android Service & Multi-App Support 33 3.4 Evaluation 34 3.4.1 Evaluation Setup 34 3.4.2 Single-App: Back-to-Back Inference 35 3.4.3 In-depth Analysis on Subgraphs 40 3.4.4 Multi-App: Dynamic Input Workloads 42 3.4.5 Power Consumption 43 3.5 Discussion 44 3.6 Summary 46 4 NetFuse: Multi-DNN Inference at the Server 47 4.1 Motivation 47 4.1.1 Multi-DNN Inference 47 4.1.2 Graph Rewriting Frameworks 50 4.2 NetFuse 51 4.2.1 Merging Individual Operations 53 4.2.2 End-to-end DNN Merging 56 4.3 Implementation 59 4.4 Evaluation 60 4.4.1 Evaluation Setup 60 4.4.2 Inference Time 62 4.4.3 Memory Footprint 64 4.5 Discussion 68 4.6 Summary 69 5 Conclusion 70 A Correctness of Merging Convolutions 84 초록 88 감사의 글 89박

해난구조 능력 분석과 실 사례 분석을 통한 구조효율성 향상에 관한 연구

The accidents at sea often bring about catastrophical situations, sometimes resulting in calamities. It is believed that such misfortunes are inevitable unless one devotes a considerable amount of attention and effort to the development of the marine activities. As of today, the marine activities are actively taking places in the Exclusive Economic Zone(EEZ) as well as in the areas of the deep-seafloor development and the South Pole. Consequently, as the accidents at sea occur more frequently, the need to sophisticate the marine salvage skills has become a crucial concern. Furthermore, a comprehensive understanding of the submergence and the sea is required to successfully perform rescue operations. For this reason, the government subsidy to enhance the performance of the marine salvage should not be limited to the Korea Navy in order to achieve interoperability between the people, government and the organizations. The Republic of Korea Navy has been contributing to the nation and the policies of the Navy by performing successful salvage operations. Nevertheless, the Korea Navy has assumed future aspects of the salvage operations with regards to the changes in unit structure upon reunification of the South and North in order to draw corresponding action plans. The military and nation's policies in support of the marine salvage are as followssecuring of the deep-ocean salvage rescue force, the integrated operating system for civil, military and government use, and the improvement of the SAR(Search and Rescue) operation system표 목차 ·························································· ⅲ 그림 목차 ························································ ⅴ ABSTRACT ···················································· ⅶ Ⅰ. 서 론 ······················································ 1 1. 연구의 필요성 및 목적 ····················································· 1 2. 연구의 범위 및 방법 ······················································· 3 Ⅱ. 해난구조 일반현황 및 역할 ································· 5 1. 해난구조 체계 ··································································· 5 2. 심해잠수 체계 ·································································· 12 3. 미래 한국 해군의 발전 양상 ················································· 20 4. 한국의 해양환경 변화 실태 ··················································· 23 Ⅲ. 해난구조 능력 분석 ······································· 29 1. 해군 해난구조 능력 ···························································· 29 2. 해난구조 전문인력 양성 능력 ·············································· 41 3. 타 기관, 외국의 해난구조 능력 ··········································· 45 Ⅳ. 해난구조 실 사례 분석 ···································· 51 1. 천안함 피격 구조작전 ························································· 51 2. 참수리-357호정 인양작전 ····················································· 59 3. 서해 훼리호 인양작전 ························································· 63 Ⅴ. 고 찰 ····················································· 69 1. 심해 구조전력 확보 운용 ····················································· 69 2. 민&#8228군 통합운용체계 구축 ·············································· 74 3. SAR 운용 협조체계 개선 ····················································· 77 Ⅵ. 결 론 ····················································· 80 참 고 문 헌 ····················································· 82관&#822

Development of a tabu search heuristic for solving multi-objective combinatorial problems with applications to constructing discrete optimal designs

Tabu search (TS) has been successfully applied for solving many complex combinatorial optimization problems in the areas of operations research and production control. However, TS is for single-objective problems in its present form. In this article, a TS-based heuristic is developed to determine Pareto-efficient solutions to a multi-objective combinatorial optimization problem. The developed algorithm is then applied to the discrete optimal design problem in statistics to demonstrate its usefulness

Tabu Search Heuristics for Solving a Class of Clustering Problems

Tabu search (TS) is a useful strategy that has been successfully applied to a number of complex combinatorial optimization problems. By guiding the search using flexible memory processes and accepting disimproved solutions at some iterations, TS helps alleviate the risk of being trapped at a local optimum. In this article, we propose TS-based heuristics for solving a class of clustering problems, and compare the relative performances of the TS-based heuristic and the simulated annealing (SA) algorithm. Computational experiments show that the TS-based heuristic with a long-term memory offers a higher possibility of finding a better solution, while the TS-based heuristic without a long-term memory performs better than the others in terms of the combined measure of solution quality and computing effort required

시스템 신뢰도의 최적화를 위한 하부시스템의 설계방법에 관한 연구

학위논문(석사) - 한국과학기술원 : 산업공학과, 1986.2, [ [iv], 61 p. ]For a series system, the problem of optimizing systems reliability under discrete design alternatives at each subsystem is initially formulated as a nonlinear 0-1 program with multiple-choice constraints. Different types of methods for achieving high systems reliability (parallel redundancy, standby redundancy, an increase in component reliability, etc.) can be easily handled as discrete design alternatives. In order to solve the problem efficiently, the nonlinear 0-1 programming problem is transformed into a linear 0-1 program. As a solution method this study presents a branch-and-bound technique with Lagrangian relaxation which provides exact optimal solutions. Further, a heuristic method by Chang and Tcha is also considered. Test problems are solved by both methods and their computational efficiencies are reported. For a class of complex systems, the possibility of obtaining a 0-1 linear program is shown, and an example problem is solved by APEX IV.한국과학기술원 : 산업공학과

최적실험계획문제와 집락문제의 해결을 위한 타부탐색에 근거한 발견적 해법의 개발

학위논문(박사) - 한국과학기술원 : 산업공학과, 1996.2, [ [v], 179 p. ]This thesis is concerned with developing algorithms for solving exact optimal design and clustering problems in statistics. To alleviate the possibility of being trapped at a local optimum, which is frequently the case in the existing algorithms, we developed Tabu search(TS)-based algorithms for both single- and multi-objective problems. We first developed TS-based algorithms for the exact optimal design and clustering problems with a single objective. We further developed TS-based direct algorithms(TSDA) which can handle multi-objective problems. TSDA is based on the difinition of Pareto-efficient solutions. Computational experiments for single-objective problems indicate that for the exact optimal problems, TS-based algorithms perform better than simulated annealing(SA) and Fedorov algorithm(FEA) in terms of the number of successes per unit time which may be considered as a combining measure of solution quality and computational efforts required, although SA is better in terms of solution quality and FEA requires less computing than the others. For the clustering problem, SA generally performs better than TS and K-Means algorithm in terms of solution quality. The K-Means algorithm requires less computing time than the others. In terms of the number of successes per unit time for complex problems, TS performs better than the others. The experimental results for multi-objective problems show that for the exact optimal design problem, TSDA is far superior to the existing algorithm. However, for the clustering problem, TSDA tends to require more computing time than the other algorithm as the number of criteria increases. In summary, TS-based algorithm are believed to be useful alternatives to the existing algorithms for solving the exact optimal design and the clustering problems in statistics. It is recommended that future research be directed towards improving the present TSDA with respect to the required amount of computing time for the clustering problem ...한국과학기술원 : 산업공학과