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
Enhancing Fidelity of P4-Based Network Emulation with a Lightweight Virtual Time System
P4’s data-plane programmability allows for highly customizable and programmable packet processing, enabling rapid innovation in network applications, such as virtualization, security, load balancing, and traffic engineering. Researchers extensively use Mininet, a popular network emulator, integrated with BMv2, for fast and flexible prototyping of these P4-based applications, but due to its lower performance in terms of throughput and latency compared to a production-grade software switch like Open vSwitch, it is crucial to have an accurate and scalable emulation testbed. In this paper, we develop a lightweight virtual time system and integrate it into Mininet with BMv2 to enhance fidelity and scalability. By scaling the time of interactions between containers and the underlying physical machine by a time dilation factor (TDF), we can trade time with system resources, making the emulated P4 network appear to be faster from the viewpoint of the switch/host processes in the container. Our experimental results show that the testbed can accurately emulate much larger networks with high loads, scaled by a factor of TDF with extremely low system overhead.
more »
« less
- PAR ID:
- 10426812
- Date Published:
- Journal Name:
- ACM SIGSIM-PADS, June 2023
- Issue:
- June 2023
- Page Range / eLocation ID:
- 34 to 43
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
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
-
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
-
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
-
Programmable networks are enabling a new class of applications that leverage the line-rate processing capability and on-chip register memory of the switch data plane. Yet the status quo is focused on developing approaches that share the register memory statically. We present NetVRM, a network management system that supports dynamic register memory sharing between multiple concurrent applications on a programmable network and is readily deployable on commodity programmable switches. NetVRM provides a virtual register memory abstraction that enables applications to share the register memory in the data plane, and abstracts away the underlying details. In principle, NetVRM supports any memory allocation algorithm given the virtual register memory abstraction. It also provides a default memory allocation algorithm that exploits the observation that applications have diminishing returns on additional memory. NetVRM provides an extension of P4, P4VRM, for developing applications with virtual register memory, and a compiler to generate data plane programs and control plane APIs. Testbed experiments show that NetVRM generalizes to a diverse variety of applications, and that its utility-based dynamic allocation policy outperforms static resource allocation. Specifically, it improves the mean satisfaction ratio (i.e., the fraction of a network application’s lifetime that it meets its utility target) by 1.6–2.2× under a range of workloads.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3573900.3591120
