Advancing Real-Time Capabilities in Cyber-Physical Systems: Core-Local Reasoning with M³
RTAS'24 invites papers that describe case studies, applications, methodologies, and algorithms contributing to the state of practice in the design, implementation, verification, validation, and evolution of time-sensitive systems. That’s where Nils Asmussen, Sebastian Haas, Adam Lackorzyński, and Michael Roitzsch presented their paper, "Core-Local Reasoning and Predictable Cross-Core Communication with M³."
Their research addresses the need for security, heterogeneity, and real-time operation in modern cyber-physical systems. While traditional real-time operating systems like FreeRTOS offer high predictability, they lack the strong component isolation necessary for platform security. Conversely, microkernels provide this isolation but complicate real-time analysis due to their use of virtual memory and privileged CPU modes.
The team introduces an alternative approach with M³, a hardware/software co-design for heterogeneous systems that ensures strong isolation between cores. The real-time capabilities of M³ had not been explored until now. To address this, researchers assessed M³’s current real-time capabilities, comparing its communication latencies with other systems and examining its unique core isolation approach.
To enhance M³'s suitability for real-time applications, they introduced network-on-chip traffic regulation and enforced resource limits. These improvements allow for local reasoning about application execution, making M³ more effective for real-time tasks.
Their evaluation, conducted using an FPGA-based hardware prototype and simulations based on gem5, demonstrates the potential of M³ to meet the demands of secure and predictable real-time systems.
The full paper is available here.
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Exploring New Horizons in Datacenters: Disaggregation-Native Data Streaming
At the 2024 ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Nils Asmussen and Michael Roitzsch presented their paper, "Towards Disaggregation-Native Data Streaming between Devices," during the 3rd Workshop on Heterogeneous Composable and Disaggregated Systems (HCDS).
Their research explores the emerging trend of disaggregation in datacenters, a method aimed at enhancing flexibility. Disaggregation involves using technologies like CXL to connect pools of CPUs, accelerators, and memory through a datacenter fabric. This setup allows applications to select the specific resources they need from these pools, optimizing performance and efficiency.
However, a challenge arises with data movement. Typically, data needs to be streamed through multiple devices, but instead of flowing directly from one device to another, it often gets staged in memory by a CPU. This staging can create delays and inefficiencies.
The researchers propose a solution: a disaggregation-native and device-independent data streaming facility. This innovation enables data to flow directly between devices without the need for intermediary staging in memory. The result is improved processing speeds and reduced latencies, making datacenters more efficient.
Their full paper can be accessed here.
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