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  1. This paper presents a framework for cloud users who wish to specify their experiments in the P4 language and map them to FPGAs in the Open Cloud Testbed (OCT). OCT consists of P4-enabled FPGA nodes that are directly connected to the network via 100 gigabit Ethernet connections, and which support runtime reconfiguration. Cloud users can quickly prototype and deploy their P4 applications through our framework, which provides the necessary infrastructure including a network interface shell for the P4 logic. We have provided several examples using this framework that demonstrate designs running at the 100 GbE line rate with the support of runtime reconfiguration for P4 functions. By combining an existing network interface shell and P4 toolchain on FPGAs, we offer a framework that enables users to rapidly execute their P4 experiments in real time on FPGAs. 
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    Free, publicly-accessible full text available May 20, 2024
  2. Many organizations maintain and operate large shared computing clusters, since they can substantially reduce computing costs by leveraging statistical multiplexing to amortize it across all users. Importantly, such shared clusters are generally not free to use, but have an internal pricing model that funds their operation. Since employees at many large organizations, especially Universities, have some budgetary autonomy over purchase decisions, internal shared clusters are increasingly competing for users with cloud platforms, which may offer lower costs and better performance. As a result, many organizations are shifting their shared clusters to operate on cloud resources. This paper empirically analyzes the user incentives for shared cloud clusters under two different pricing models using an 8-year job trace from a large shared cluster for a large University system. Our analysis shows that, with either pricing model, a large fraction of users have little financial incentive to participate in a shared cloud cluster compared to directly acquiring resources from a cloud platform. While shared cloud clusters can provide some limited reductions in cost by leveraging reserved instances at a discount, due to bursty workloads, realizing these reductions generally requires imposing long job waiting times, which for many users are likely not worth the cost reduction. In particular, we show that, assuming users defect from the shared cluster if their wait time is greater than 15x their average job runtime, over 80% of the users would defect, which increases the price of the remaining users such that it eliminates any incentive to participate in a shared cluster. Thus, while shared cloud clusters may provide users other benefits, their financial incentives are weak. 
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    Free, publicly-accessible full text available April 15, 2024
  3. This paper presents a framework for cloud users who wish to specify their experiments in the P4 language and map them to FPGAs in the Open Cloud Testbed (OCT). OCT consists of P4-enabled FPGA nodes that are directly connected to the network via 100 gigabit Ethernet connections, and which support runtime reconfiguration. Cloud users can quickly prototype and deploy their P4 applications through our framework, which provides the necessary infrastructure including a network interface shell for the P4 logic. We have provided several examples using this framework that demonstrate designs running at the 100 GbE line rate with the support of runtime reconfiguration for P4 functions. By combining an existing network interface shell and P4 toolchain on FPGAs, we offer a framework that enables users to rapidly execute their P4 experiments in real time on FPGAs. 
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    Free, publicly-accessible full text available May 1, 2024
  4. This paper presents a framework for cloud users who wish to specify their experiments in the P4 language and map them to FPGAs in the Open Cloud Testbed (OCT). OCT consists of P4-enabled FPGA nodes that are directly connected to the network via 100 gigabit Ethernet connections, and which support runtime reconfiguration. Cloud users can quickly prototype and deploy their P4 applications through our framework, which provides the necessary infrastructure including a network interface shell for the P4 logic. We have provided several examples using this framework that demonstrate designs running at the 100 GbE line rate with the support of runtime reconfiguration for P4 functions. By combining an existing network interface shell and P4 toolchain on FPGAs, we offer a framework that enables users to rapidly execute their P4 experiments in real time on FPGAs. 
    more » « less
    Free, publicly-accessible full text available April 1, 2024
  5. This paper presents a framework for cloud users who wish to specify their experiments in the P4 language and map them to FPGAs in the Open Cloud Testbed (OCT). OCT consists of P4-enabled FPGA nodes that are directly connected to the network via 100 gigabit Ethernet connections, and which support runtime reconfiguration. Cloud users can quickly prototype and deploy their P4 applications through our framework, which provides the necessary infrastructure including a network interface shell for the P4 logic. We have provided several examples using this framework that demonstrate designs running at the 100 GbE line rate with the support of runtime reconfiguration for P4 functions. By combining an existing network interface shell and P4 toolchain on FPGAs, we offer a framework that enables users to rapidly execute their P4 experiments in real time on FPGAs. 
    more » « less
    Free, publicly-accessible full text available April 1, 2024
  6. Free, publicly-accessible full text available May 20, 2024
  7. Free, publicly-accessible full text available May 1, 2024
  8. Weather sensing and forecasting has become increasingly accurate in the last decade thanks to high-resolution radars, efficient computational algorithms, and high-performance computing facilities. Through a distributed and federated network of radars, scientists can make high-resolution observations of the weather conditions on a scale that benefits public safety, commerce, transportation, and other fields. While weather radars are critical infrastructure, they are often located in remote areas with poor network connectivity. Data retrieved from these radars are often delayed or lost, or even lack proper synchronization, resulting in sub-optimal weather prediction. This work applies Named Data Networking (NDN) to a federation of weather sensing radars for efficient content addressing and retrieval. We identify weather data based on a hierarchical naming scheme that allows us to explicitly access desired files. We demonstrate that compared to the window-based mechanism in TCP/IP, an NDN based mechanism improves data quality, reduces uncertainty, and enhances weather prediction. 
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