2021 — 2026 |
Banerjee, Suman (co-PI) [⬀] Zhong, Lin Carin, Lawrence (co-PI) [⬀] Chen, Yiran [⬀] Pajic, Miroslav (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Ai Institute For Edge Computing Leveraging Next Generation Networks (Athena)
The National AI Institute, named Athena, seeks to kindle and fuel a transformation in modern edge computing by leveraging next generation networks. Led by Duke University, Athena taps the ongoing revolution in Artificial Intelligence (AI) and brings together a multidisciplinary team from seven universities: Duke University, Massachusetts Institute of Technology, North Carolina Agricultural and Technical State University, Princeton University, University of Michigan-Ann Arbor, University of Wisconsin-Madison, and Yale University. Athena organizes its research activities under four interrelated thrusts - AI, Computer Systems, Networking, and Services - which constitute an ambitious and comprehensive research agenda. It will develop AI-driven, next generation technologies for edge computing and new algorithmic and practical foundations of AI. Athena will evaluate the research outcomes through a combination of analytical, experimental, and empirical instruments, especially with target use-inspired research. Athena is committed to a robust and comprehensive suite of educational and workforce development endeavors alongside its collaboration and knowledge transfer efforts with external stakeholders that include both industry and community partnerships. Athena aims at scientific contributions in both edge computing and AI. These include (i) edge networking mechanisms across the stack by leveraging a data-driven, AI-based approach; (ii) systems support for efficient and reliable AI across the edge-enhanced mobile networks; (iii) novel practical and algorithmic foundations of AI to ensure the new functionalities, efficiency, scalability, security, privacy, and fairness of the AI solutions adopted in these next-generation networks; and (iv) novel services and applications, focused on diverse cyber-physical systems that leverage the innovations of the other thrusts. Athena’s research outcomes will benefit the network and computer industries at large. This national institute will work closely with external collaborators to translate research outcomes to industrial practice and policymaking. The educational and outreach activities of Athena will empower students and postdocs to develop their interests, build skills, and acquire knowledge about AI and computer and network systems through research experiences, industry internships, and community engagements. The Inclusive AI Initiative – one of Athena’s innovations in education and workforce development - will strengthen the ethical AI competencies of all Athena members to better promote and be aware of equity and fairness in their research and the communities impacted by the institute’s research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.97 |
2021 — 2024 |
Zhong, Lin |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Cns Core: Small: Disentangled System Software
Today's system software are large and vastly complex. While they are highly modular, their components are often interdependent and tightly coupled. As a result, system software, especially operating systems (OSes), have become difficult to maintain, evolve, update safely, and run reliably. This is particularly problematic in environments where reliability is necessary, yet hardware redundancy is expensive or impossible. For example, system software updates must be painstakingly applied without downtime or lost execution context in pacemakers and space probes. Even in data centers, where network switches are replicated for reliability, switch software failures and maintenance updates still lead to network outages. The key insight of the project is that state spill between modules is the root cause of entanglement within system software. State spill happens when one module's state undergoes a lasting change as a result of interacting with another module. It is both prevalent and deep in modern system software. By minimizing state spill, this project aims at disentangled system software in which every component can evolve independently, ideally at runtime, without the fear of failures in one component jeopardizing others. Today's cloud services achieve fault tolerance and timely evolution with massive redundancy and abundance in warehouse data centers. This project will help bring these values to computer systems where redundancy and abundance are a luxury, such as medical implants, embedded systems, and even edge data centers, substantially improving their availability. By elevating these computers to the same level as data centers, this project will encourage more services to be placed outside the cloud, closer to end users, a radical departure from today's cloud-centric paradigm. This departure not only has the potential for better user experiences and novel services but also to democratize computing. The project will also cross-pollinate other important directions in systems software research by motivating new language features and suggest more ways to ensure disentanglement statically, and by allowing incremental specification and verification of large software systems on a module-by-module basis. The project will provide a platform to engage undergraduate students and high-school students in computing research, especially women and underrepresented minorities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.97 |
2021 — 2022 |
Shao, Zhong [⬀] Zhong, Lin Bhattacharjee, Abhishek (co-PI) [⬀] Khandelwal, Anurag |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Pposs: Planning: High-Performance Certified Trust For Global-Scale Applications
A global-scale public infrastructure of distributed computing resources, in the form of data centers of various scales, has emerged in the past decade. Today, a user of this global infrastructure must trust the infrastructure vendors based on their informal textual contracts. This trust model provides limited legal protection of user interests and has become a key barrier for more services to migrate into the public infrastructure, stymieing innovation and competition. This project's key novelty is to build highly performant, certified execution environments (CEEs) for large-scale distributed systems. In doing so, the project explores, refines, and discovers design principles for scaling certified trust --- specifically, scaling up to include the entire software stack, and scaling out to include globally distributed resources. The project's main impact is to enable and promote trustworthy, performant, cost-effective uses of the public global infrastructure, empowering applications and services for a global market. Specifically it will lower the barrier of entrance for startups to enter a global market and as a result, foster competition and innovation, and make information technologies more accessible. It is intended to profoundly change many industries that traditionally heavily rely on proprietary IT infrastructures, e.g., mobile networks.
The project makes three related scientific contributions. First, it contributes new technologies for building distributed CEE enclaves for running global-scale applications. CEEs extend remote attestation (as in trusted execution environments (TEEs)) with formal verification so the chain of trust can be used to establish not only the authenticity of enclave binaries but also the trustworthiness properties. Second, it provides hardware and software support to accelerate the underlying mechanisms for isolation, integrity, and confidentiality. These themes range from support for better isolation to CPUs and TEEs, but also include fast mechanisms for emerging hardware accelerators. Finally, the team of researchers explores the extension of certifiably trustworthy execution environments to emerging disaggregated datacenter designs using a software-defined-network-based decomposition of functionalities. The insights gleaned from their study guide the development of new algorithm-driven, data structure-driven, and hardware-driven solutions for the trustworthy disaggregated cloud design. During the Planning stage, the investigators are developing a prototype testbed to evaluate the feasibility of building a high-performance trustworthy global-scale mobile network using cloud-scale disaggregated CEEs. They are compiling a list of challenges which become the central research agenda for a full-scale, large proposal.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.97 |
2022 — 2025 |
Zhong, Lin |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Collaborative Research: Cns Core: Medium: Softwarizing Millimeter-Wave Radio Access Networks (Rans) At the Edge
Emerging applications in augmented reality, connected autonomous vehicles, and industrial IoT systems impose demanding requirements on next-generation mobile networks that can hardly be met alone with radio resources below 7 GHz. Therefore, 5G and beyond networks have embraced radios operating in millimeter-wave (mmWave) frequency bands, which offer 25 times or more bandwidth worldwide. On the other hand, mmWave radio networks require the dense deployment of infrastructure nodes to achieve desirable coverage, because mmWave radio signals suffer from high propagation loss and are vulnerable to blockage and mobility. Unfortunately, mmWave infrastructure nodes, e.g., gNodeB in 5G, are made of specialized, dedicated hardware and as a result, their dense deployment would incur formidable capital and operational cost. The goal of the proposed project is to reduce the cost of mmWave radio infrastructure nodes by softwarizing their radio access network (RAN) functions and serving them from data centers close to end users, i.e., edge data centers, therefore facilitating network densification. More importantly, it will allow for previously impossible flexibility in network implementation and configuration as well as efficiency in resource allocation across the network and the edge data center. At the societal level, this project will fuel the ongoing revolution of mobile network virtualization and accelerate the development and deployment of next-generation network systems.<br/><br/>The key insight toward addressing the challenges associated with softwarizing mmWave RANs at the edge is to exploit the massive data parallelism inside the mmWave baseband and its inherent structures, with programmable hardware in all domains. The project targets the following scientific contributions in three interrelated research thrusts. (i) A low-latency software realization of the mmWave physical layer for commodity server clusters suitable for edge deployment. (ii) Adaptive RAN configuration and in-network compression schemes that cope with the limited fronthaul capacity in practice, without substantially increasing the cost of mmWave infrastructure nodes. (iii) Novel sensing and imaging schemes based on mmWave radio signals intended for communications. These include sensing with a single mmWave infrastructure node and sensing that leverages multiple coordinated mmWave nodes to achieve previously impossible coverage and resolution.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.97 |
2022 — 2025 |
Zhong, Lin Puri, Shruti Schoelkopf, Robert (co-PI) [⬀] Ding, Yongshan Bhattacharjee, Abhishek (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Mri: Development of Paragon: Control Instrument For Post Nisq Quantum Computing
This project will design and implement PARAGON, an instrument of control systems for superconducting circuit-based quantum computers. Using an ultra-low latency, scalable network of Field-Programmable Gate Array (FPGA) accelerators, PARAGON will support real-time measurement, error correction, and control of 100s of qubits. The project will also develop the necessary systems, programming and debugging support for realizing and evaluating new quantum hardware and algorithms with PARAGON. PARAGON will substantially advance the Nation’s research capabilities in quantum computing, enabling operational tests of error-corrected algorithms and accelerating the arrival of fault-tolerant quantum computing.<br/><br/>Toward cost-effective scalability, PARAGON employs a balanced, fat tree to organize the large number of building blocks and to distribute data, clock, and time (trigger). The leaves of the tree feature Radio Frequency System-on-Chip (RFSoC) for quantum control and the internal nodes of the tree Multiprocessor System-on-Chip (MPSoC) for integration. PARAGON will empower two broad research communities that tackle quantum computing from different fronts. It will allow Physicists to investigate the theory and realization of better qubits, and experiment with sophisticated error correction and fault tolerance methods on real qubits, at a previously impossible scale. It will allow Computer Scientists to experiment with novel architectures and programming schemes for quantum control. Most importantly, it will serve as the meeting place for both communities, fostering cross-pollination and catalyzing collaboration. Through its open design and open-source software, PARAGON will empower the broad community of academic and industrial researchers in superconducting quantum computing to experiment in previously impossible ways. While PARAGON will be implemented for quantum computers based on superconducting circuits, its design can be adapted for those based on other technologies, which also face similar challenges in their control systems. It will provide critical know-how to the budding industry of quantum control systems so that the latter can further lower the cost for wider, commercial availability. The instrument will advance research agendas in multiple disciplines, creating opportunities in cross pollination between applied physics, computer science and engineering. It will create new opportunities to engage both graduate and undergraduate students, especially underrepresented minorities and women, providing unique training for multidisciplinary research. Source materials produced by the project can be found at https://github.com/yale-paragon. The repositories will be actively maintained by the project team during the award period. During the lifetime of PARAGON, the repositories will transition into community-based development and maintenance with the project team being one of the contributors. The project team will ensure the repositories are available at least five years after the lifetime of the physical testbed of PARAGON.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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0.97 |