6G-life

With research beginning on the next generation of mobile communications 6G, TUM joins forces with TU Dresden in the BMBF funded project 6G-life to develop new approaches regarding sustainability, security, resilience and latency in mobile communications.

Hereby, LIS is engaged in exploring new architectures and architecture extensions for network interface cards (NICs) in processing nodes. This is part of the chairs endeavor to investigate how much intelligence can be brought to the network interface, taking into account the specific needs of certain networking domains and applications.

Research Focus

Many 6G applications, such as extended reality (XR) or autonomous driving, will require low latency control loops to be closed over the network, thereby requiring processing near the user and decision-making early in the data path. This leads to a large increase in Edge Computing and a growing amount of differently dimensioned, heterogenous processing nodes. Since changing user and application behaviour can exert very volatile traffic characteristics and processing requirements, such processing nodes have to interact with the network adaptively and energy-efficiently, also to avoid overprovisioning single nodes.

Therefore, we at LIS want to explore how to extract information on current traffic characteristics and processing requirements in the NIC and how to use this information to efficiently provision the servers processing resources and reflexively react to changing conditions. More concretely, this involves:

  • designing a packet processing architecture with the required logic to extract information from incoming traffic
  • performing power management of the host CPU and its heterogenous resources
  • making processing decisions early in the data path, reducing the load on the CPU

and much more. We are prototyping these contributions on FPGA-based NICs in a multi-server testbed at our chair.

6G Testbed

The LIS 6G Testbed and Demonstrator consists of 2 AMD Epyc Server nodes and 4 AMD Ryzen PC nodes, which are equipped with several Xilinx FPGAs (NetFPGA SUME and Alveo), as well as commercial Intel NICs. They are used for prototyping 6G-specific SmartNIC extensions, providing proof-of-concept evaluation and demonstration in a physical networking testbed. The nodes can be used in a variety of ways, depending on the specific use case and evaluation setup. The figure on the right shows an exemplary representation of the nodes in a typical 6G use case.

Involved Researchers

Marco Liess

Klajd Zyla

Franz Biersack

Student Work

Offered Topics

Are you interested in contributing to 6G-life? If you don't find an interesting topic listed here, sometimes there is also the possibility to define a topic matching your specific interests. If you have questions about the 6G-life project and student works at our chair, please contact Marco Liess.

Ongoing

Exploring Power Management of AMD Processors in Linux

Description

With the advent of research on the next generation of mobile communications 6G, LIS is engaged in exploring architectures and architecture extensions for networking hardware. In order to research on energy-efficient and low-latency network interfaces for next-generation networks, we are setting up a hardware testbed with FPGA-based Network Interface Accelerator Cards and AMD Epyc and Ryzen Processors.

The incoming traffic load and with it the computing requirements on network processing nodes such as edge servers can span multiple magnitudes in a matter of milliseconds and less. The systems are ususally dimensioned to cope with peak loads, resulting in a low resource utilization when traffic is little. To ensure a highly energy-efficient resource utilization, dynamic power management with respect to fluctuating processing requirements is necessary to reduce the power consumption (e.g. by dynamic voltage frequency scaling (DVFS) or power gating) in times of low traffic load.

The goal of this work is to explore Linux power management possibilities on AMD processors. This involves researching possible power management options (e.g. DVFS) in Linux, understanding and using the provided API, verifying the correct functionality and setting up a framework for measurement and benchmarking. The measurements shall be processed and evaluated concerning key performance indicators like power consumption, switching delay, etc.

Prerequisites

  • Good experience with Linux, Command Line Tools and Bash scripting
  • Programming skills in C and Python
  • Preferably practical experience with the Linux Kernel, Kernel tracing functionality and low-level software
  • Solid understanding of operating system concepts and hardware/software interactions

Contact

Marco Liess, M.Sc.

Tel.: +49.89.289.23873
Raum: N2139
Email: marco.liess@tum.de

 

Supervisor:

Marco Liess

Bring-up and Evaluation of DPDK Network Driver for FPGA-based Networking

Description

With the advent of research on the next generation of
mobile communications 6G, LIS is engaged in exploring
architectures and architecture extensions for networking
hardware. In order to research on energy-efficient and
low-latency network interfaces for next-generation
networks, we are setting up a hardware testbed with
FPGA-based Network Interface Accelerator Cards in the
form of Xilinx Alveo and NetFPGA SUME FPGA boards.
This requires the bring-up and evaluation of the  HDL
Design, the Linux kernel drivers and applications.

OpenNIC provides open-source code for an HDL design and kernel driver as basis for a custom hardware network interface on FPGAs. The goal of this work is to setup the Linux DPDK driver to interface with the HDL design on the FPGA, validate the communication with the FPGA and correct functionality of the driver and finally evaluate the driver, especially with comparison to the standard Linux network driver. This can involve establishing a test setup with additional postprocessing regarding key performance indicators (KPIs) such as latency, bandwidth, memory footprint, etc., and tracing of the drivers and Linux network stack.

 

Prerequisites

- Good experience with Linux, Command Line Tools and Bash scripting
- Programming skills in C and Python (and VHDL)
- Knowledge of Internet Networking Technologies, in particular OSI layer protocols

Contact

Marco Liess, M.Sc.

Tel.: +49.89.289.23873
Raum: N2139
Email: marco.liess@tum.de

Supervisor:

Marco Liess
Completed

Contact

Marco Liess, M.Sc.

Tel.: +49.89.289.23873
Raum: N2139
Email: marco.liess@tum.de

 

Supervisor:

Marco Liess

Contact

Marco Liess, M.Sc.

Tel.: +49.89.289.23873
Gebäude: N1 (Theresienstr. 90)
Raum: N2139
Email: marco.liess@tum.de

 

Supervisor:

Marco Liess

Contact

Marco Liess, M.Sc.

Technische Universität München
Lehrstuhl für Integrierte Systeme
Arcisstr. 21, 80333 München

Tel.: +49.89.289.23873
Raum: N2139
Email: marco.liess@tum.de

 

Supervisor:

Marco Liess

Publications

  • Marco Liess, Julian Demicoli, Tobias Tiedje, Matthias Lohrmann, Matthias Nickel, Marco Luniak, Dimitris Prousalis, Thomas Wild, Ronald Tetzlaff, Diana Göhringer, Christian Mayr, Karlheinz Bock, Sebastian Steinhorst, Andreas Herkersdorf: X-MAPE: Extending 6G-connected Self-adaptive Systems with Reflexive Actions. 2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), 2023 more… BibTeX