High-speed, in-band performance measurement instrumentation for next generation IP networks

Facilitating always-on instrumentation of Internet traffic for the purposes of performance measurement is crucial in order to enable accountability of resource usage and automated network control, management and optimisation. This has proven infeasible to date due to the lack of native measurement mechanisms that can form an integral part of the network‟s main forwarding operation. However, Internet Protocol version 6 (IPv6) specification enables the efficient encoding and processing of optional per-packet information as a native part of the network layer, and this constitutes a strong reason for IPv6 to be adopted as the ubiquitous next generation Internet transport. In this paper we present a very high-speed hardware implementation of in-line measurement, a truly native traffic instrumentation mechanism for the next generation Internet, which facilitates performance measurement of the actual data-carrying traffic at small timescales between two points in the network. This system is designed to operate as part of the routers' fast path and to incur an absolutely minimal impact on the network operation even while instrumenting traffic between the edges of very high capacity links. Our results show that the implementation can be easily accommodated by current FPGA technology, and real Internet traffic traces verify that the overhead incurred by instrumenting every packet over a 10 Gb/s operational backbone link carrying a typical workload is indeed negligible

BOiLS: Bayesian Optimisation for Logic Synthesis

Optimising the quality-of-results (QoR) of circuits during logic synthesis is a formidable challenge necessitating the exploration of exponentially sized search spaces. While expert-designed operations aid in uncovering effective sequences, the increase in complexity of logic circuits favours automated procedures. To enable efficient and scalable solvers, we propose BOiLS, the first algorithm adapting Bayesian optimisation to navigate the space of synthesis operations. BOiLS requires no human intervention and trades-off exploration versus exploitation through novel Gaussian process kernels and trust-region constrained acquisitions. In a set of experiments on EPFL benchmarks, we demonstrate BOiLS's superior performance compared to state-of-the-art in terms of both sample efficiency and QoR values

Economic growth and corporate renewal

To address competition from Emerging and Industrialized Countries it is necessary for Italian companies to face structural and financial reforms. Structural reforms will affect and improve processes, products. They will upgrade knowledge transfer. At the same time, financial reforms are necessary to adjust firms’ dimensions with what markets and international competition require. A movement in the right direction is the rise of innovative medium firms. These corporations are spreading through affiliation networks which improve the systemic efficiency and that are responsible for the progressive deep changes in the industry. Italy’s growth strategy will call for appropriate industrial policies and supported by a widespread socioeconomic consensus.internationalization, technological change, international trade, emerging countries.

Autonomous Vehicle Coordination with Wireless Sensor and Actuator Networks

A coordinated team of mobile wireless sensor and actuator nodes can bring numerous benefits for various applications in the field of cooperative surveillance, mapping unknown areas, disaster management, automated highway and space exploration. This article explores the idea of mobile nodes using vehicles on wheels, augmented with wireless, sensing, and control capabilities. One of the vehicles acts as a leader, being remotely driven by the user, the others represent the followers. Each vehicle has a low-power wireless sensor node attached, featuring a 3D accelerometer and a magnetic compass. Speed and orientation are computed in real time using inertial navigation techniques. The leader periodically transmits these measures to the followers, which implement a lightweight fuzzy logic controller for imitating the leader's movement pattern. We report in detail on all development phases, covering design, simulation, controller tuning, inertial sensor evaluation, calibration, scheduling, fixed-point computation, debugging, benchmarking, field experiments, and lessons learned

Synthetic biology: advancing biological frontiers by building synthetic systems

Advances in synthetic biology are contributing to diverse research areas, from basic biology to biomanufacturing and disease therapy. We discuss the theoretical foundation, applications, and potential of this emerging field

유전알고리즘 및 강화학습을 사용한 고속 회로 설계 자동화 프레임워크

학위논문(석사) -- 서울대학교대학원 : 융합과학기술대학원 지능정보융합학과, 2022.2. 전동석.Although design automation is a key enabler of modern large-scale digital systems, automating the transistor-level circuit design process still remains a challenge. Some recent works suggest that deep learning algorithms could be adopted to find optimal transistor dimensions in relatively small circuitry such as analog amplifiers. However, those approaches are not capable of exploring different circuit structures to meet the given design constraints. In this work, we propose an automatic circuit design framework that can generate practical circuit structures from scratch as well as optimize the size of each transistor, considering performance and reliability. We employ the framework to design level shifter circuits, and the experimental results show that the framework produces novel level shifter circuit topologies and the automatically optimized designs achieve 2.8-5.3× lower PDP than prior arts designed by human experts.설계 자동화는 대규모 디지털 시스템을 가능하게 하는 핵심 요소이지만 트랜지스터 수준에서 회로 설계 프로세스를 자동화하는 것은 여전히 어려운 과제로 남아 있습니다. 최근 연구에서는 아날로그 앰프와 같은 비교적 작은 회로에서 최적의 성능을 보이는 트랜지스터 크기를 찾기 위해 deep learning 알고리즘을 활용할 수 있다고 말합니다. 그러나 이러한 접근 방식은 주어진 설계 constraint를 충족하는 다른 회로 구조 탐색에 적용하기 어렵습니다. 본 연구에서는 성능과 신뢰성을 고려하여 각 트랜지스터의 크기를 최적화할 뿐만 아니라 처음부터 실용적인 회로 구조를 생성할 수 있는 자동 회로 설계 framework를 제안합니다. 우리는 framework를 사용하여 level shifter 회로를 설계했으며 실험 결과는 프레임워크가 새로운 level shifter 회로 토폴로지를 생성하고 자동으로 최적화된 설계가 인간 전문가가 설계한 선행 기술보다 2.8-5.3배 더 낮은 PDP를 달성한다는 것을 보여줍니다.Abstract i Contents ii List of Tables iv List of Figures v List of Algorithms vi 1 Introduction 1 2 Related work 6 2.1 Genetic Algorithm 6 2.2 NeuroEvolution of Augmenting Topologies (NEAT) 7 2.3 Reinforcement Learning (RL) 10 2.4 DDPG, D4PG, and PPO 12 2.5 Level Shifter 14 3 Proposed circuit design framework 17 3.1 Topology Generator 17 3.2 Circuit Optimizer 25 4 Experiment Result 32 4.1 Level Shifter Design 32 4.2 Topology Generation 34 4.3 Circuit Optimization 36 4.4 Test Chip Fabrication 42 4.5 Applicability of Topology Generator 47 5 Conclusion 50 Abstract (In Korean) 57석