The future of computing beyond Moore's Law.

Moore's Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore's Law for 50 years is failing and is anticipated to flatten by 2025. This article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'

Special Topics in Information Technology

This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

Special Topics in Information Technology

This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

SDT: A Low-cost and Topology-reconfigurable Testbed for Network Research

Network experiments are essential to network-related scientific research (e.g., congestion control, QoS, network topology design, and traffic engineering). However, (re)configuring various topologies on a real testbed is expensive, time-consuming, and error-prone. In this paper, we propose \emph{Software Defined Topology Testbed (SDT)}, a method for constructing a user-defined network topology using a few commodity switches. SDT is low-cost, deployment-friendly, and reconfigurable, which can run multiple sets of experiments under different topologies by simply using different topology configuration files at the controller we designed. We implement a prototype of SDT and conduct numerous experiments. Evaluations show that SDT only introduces at most 2\% extra overhead than full testbeds on multi-hop latency and is far more efficient than software simulators (reducing the evaluation time by up to 2899x). SDT is more cost-effective and scalable than existing Topology Projection (TP) solutions. Further experiments show that SDT can support various network research experiments at a low cost on topics including but not limited to topology design, congestion control, and traffic engineering.Comment: This paper will be published in IEEE CLUSTER 2023. Preview version onl

Nanophotonic design and nanomaterial assembly for next-generation optoelectronics

Nanomaterials are widely deployed in many optoelectronic technologies, with applications in solar energy harvesting, light emission, bio-sensing, computing and communications. The unique advantages of colloidal nanomaterials include size-tunable optical properties and room-temperature solution-processability, which translates to low-cost materials growth and fabrication processes associated with nanomaterials-based technology. Moreover, their lightweight and thin-film nature enables optoelectronic devices made from nanomaterials to be flexibly coated on almost any surface, which is ideal for applications such as wearable electronics and building-integrated photovoltaics. This thesis focuses on combining optical modeling, nanomaterials synthesis, nanofabrication, and advanced optical and electrical characterization techniques to develop nanomaterial-based next-generation optoelectronic devices. The first section of this thesis focuses on applying nanophotonics design principles to optically engineer solar cell and photodetector device structures for specific applications. One of our studies demonstrated a high-performing visible-blind ultraviolet (UV) thin film photodetector by introducing nanoheterojunctions for enhanced absorption and carrier injection. In another study, we used optical simulations and an effective medium model to investigate and predict light-trapping enhancements by embedding plasmonic nano-inclusions in the absorbing layer of solution-processed solar cells. We also combined thin-film interference engineering and multi-objective optimization algorithms to control the color and transparency of colloidal quantum dot (CQD) solar cells for applications in building-integrated photovoltaics and multi-junction photovoltaics. In the final study of this section, we proposed and investigated engineering photonic bands in strongly absorbing materials to tune the spectral selectivity of optoelectronic films. We then focus on developing lead sulfide CQD-based light emitting diodes (QLEDs) and solar cells with novel functionality. We developed a room-temperature-processed silver-nanowire-based transparent electrode for flexible optoelectronics. With carefully-tuned nanomaterials synthesis conditions, we fabricated PbS QLEDs with near-infrared emission that can be easily detected by inexpensive silicon-based photodetectors, paving the way for our proposed flexible transparent light emitting membrane technology, which has many target applications including in next-generation virtual reality googles and motion-capture suits for the film industry. We also built a semi-automated spray-casting system to demonstrate an all-solution-processed CQD solar cell, as a scalable and portable method for manufacturing CQD solar cells, expanding the application areas of this technology

Characterizing and Utilizing the Interplay between Quantum Technologies and Non-Terrestrial Networks

Quantum technologies have been widely recognized as one of the milestones towards the ongoing digital transformation, which will also trigger new disruptive innovations. Quantum technologies encompassing quantum computing, communications, and sensing offer an interesting set of advantages such as unconditional security and ultra-fast computing capabilities. However, deploying quantum services at a global scale requires circumventing the limitations due to the geographical boundaries and terrestrial obstacles, which can be adequately addressed by considering non-terrestrial networks (NTNs). In the recent few years, establishing multi-layer NTNs has been extensively studied to integrate space-airborne-terrestrial communications systems, particularly by the international standardization organizations such as the third-generation partnership project (3GPP) and the international telecommunication union (ITU), in order to support future wireless ecosystems. Indeed, amalgamating quantum technologies and NTNs will scale up the quantum communications ranges and provide unprecedented levels of security and processing solutions that are safer and faster than the traditional offerings. This paper provides some insights into the interplay between the evolving NTN architectures and quantum technologies with a particular focus on the integration challenges and their potential solutions for enhancing the quantum-NTN interoperability among various space-air-ground communications nodes. The emphasis is on how the quantum technologies can benefit from satellites and aerial platforms as an integrated network and vice versa. Moreover, a set of future research directions and new opportunities are identified

Energy-efficient architectures for chip-scale networks and memory systems using silicon-photonics technology

Today's supercomputers and cloud systems run many data-centric applications such as machine learning, graph algorithms, and cognitive processing, which have large data footprints and complex data access patterns. With computational capacity of large-scale systems projected to rise up to 50GFLOPS/W, the target energy-per-bit budget for data movement is expected to reach as low as 0.1pJ/bit, assuming 200bits/FLOP for data transfers. This tight energy budget impacts the design of both chip-scale networks and main memory systems. Conventional electrical links used in chip-scale networks (0.5-3pJ/bit) and DRAM systems used in main memory (>30pJ/bit) fail to provide sustained performance at low energy budgets. This thesis builds on the promising research on silicon-photonic technology to design system architectures and system management policies for chip-scale networks and main memory systems. The adoption of silicon-photonic links as chip-scale networks, however, is hampered by the high sensitivity of optical devices towards thermal and process variations. These device sensitivities result in high power overheads at high-speed communications. Moreover, applications differ in their resource utilization, resulting in application-specific thermal profiles and bandwidth needs. Similarly, optically-controlled memory systems designed using conventional electrical-based architectures require additional circuitry for electrical-to-optical and optical-to-electrical conversions within memory. These conversions increase the energy and latency per memory access. Due to these issues, chip-scale networks and memory systems designed using silicon-photonics technology leave much of their benefits underutilized. This thesis argues for the need to rearchitect memory systems and redesign network management policies such that they are aware of the application variability and the underlying device characteristics of silicon-photonic technology. We claim that such a cross-layer design enables a high-throughput and energy-efficient unified silicon-photonic link and main memory system. This thesis undertakes the cross-layer design with silicon-photonic technology in two fronts. First, we study the varying network bandwidth requirements across different applications and also within a given application. To address this variability, we develop bandwidth allocation policies that account for application needs and device sensitivities to ensure power-efficient operation of silicon-photonic links. Second, we design a novel architecture of an optically-controlled main memory system that is directly interfaced with silicon-photonic links using a novel read and write access protocol. Such a system ensures low-energy and high-throughput access from the processor to a high-density memory. To further address the diversity in application memory characteristics, we explore heterogeneous memory systems with multiple memory modules that provide varied power-performance benefits. We design a memory management policy for such systems that allocates pages at the granularity of memory objects within an application

Enhancing Network Slicing Architectures with Machine Learning, Security, Sustainability and Experimental Networks Integration

Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.Comment: 10 pages, 11 figure

Engineering Tunable Colloidal Nanostructures for Light Energy Harvesting

Colloidal nanomaterials, such as semiconductor quantum dots and plasmonic metal nanoparticles, are of interest for various optoelectronic applications due to their size-tunable optical properties, unique electronic structures, and low-cost fabrication techniques. As the physical footprint of emerging optoelectronic device components continues to shrink, colloidal nanomaterials have the potential to enable advances in fields such as low-power computing, renewable energy generation and storage, and biosensing and medicine, due to their small size, earth-abundance, and novel functionality. This thesis focuses on engineering these nanostructures for energy harvesting technologies, such as solar cells, photodetectors and photocatalysts. This is achieved by combining modeling, nanofabrication, and advanced optical and electrical characterization techniques. The study is implemented in three sections. The first involves engineering these nanostructures for solution processed solar cells. Using optimization algorithms combined with thin film interference modeling, we developed a method for producing arbitrary spectral profiles in solar cells structures for potential applications in building- and window-integrated power generation. Similarly, by using photonic band engineering in strongly absorbing materials, we developed and analyzed a new strategy for tuning the spectral selectivity of optoelectronic films. Additionally we critically evaluate the prospects for plasmonic enhancements in solution-processed thin-film solar cells by developing an intuitive effective medium model for embedded plasmonic nanostructures in photovoltaic thin films. The next section involves investigating these nanostructures for photon detection applications. One study involves using a one-step solution-based growth technique to grow antimony selenide nanowires. This enables the growth of high-quality antimony selenide nanostructures from a molecular ink directly on flexible substrates for high-performance near-infrared photodetectors thus providing a route for low-cost, flexible, and broadband photon detection. The other study demonstrates high responsivity visible blind photodetectors based on nanoheterojunction films, thus representing a viable path for building UV cost-effective optoelectronic devices Finally, the last section includes designing, developing and characterizing new plasmonic-catalytic systems based on earth-abundant and cost-effective nanomaterials such as aluminum. We present the first photophysical characterization of plasmonic aluminum nanoparticles, and identify tuning strategies such as surface modifications for various niche applications. These three sections culminate in creating a sustainable route to building both an energy-efficient and scalable-materials platform for the next generation of nanotechnology-based optoelectronic devices for energy applications