Modern data-centre workloads (e.g., agentic AI) demand strong security guarantees and high performance, which come today at a high resource cost: data-centre hardware and software infrastructures exhibit significant memory footprints and use large amounts of CPU cycles and energy. This trade-off is untenable: the environmental impact of computing is rising, energy and hardware costs are climbing, and the industry urgently needs computer systems that are more frugal without sacrificing security and performance.
The goal of this PhD is to design and implement a lightweight operating system (OS) capable of running modern data-centre workloads on emerging minimal hardware. The solution should 1) cut resource consumption relative to traditional approaches; 2) improve security by strengthening isolation guarantees; 3) match or exceed the performance of conventional solutions; and 4) remain transparently compatible with existing workloads.
Minimal, MMU-less (without a Memory Management Unit) hardware is attractive for resource efficiency and performance. Although historically confined to small embedded devices, such hardware has recently gained capability-based architectural extensions that remove the security barriers previously excluding it from running data-centre workloads. However, combining capabilities with the absence of an MMU introduces significant compatibility challenges: the OS’s isolation model and memory management must be reworked to recover key functionalities normally provided by MMU hardware. The project should extend NoMMU Linux by bringing back these crucial functionalities in the form of three contributions:
Process duplication. Building on our prior work enabling fast, lightweight duplication within a single virtual address space, we will construct a NoMMU Linux-based OS that leverages the target hardware’s capability features to restore transparent copy-on-write process duplication within a single physical address space.
Memory allocation and compaction. Without an MMU, fragmentation is expected to be a major obstacle to efficient memory use. We will design allocation and compaction algorithms exploiting capability hardware’s pointer-tracking to safely relocate data within a physical address space and optimise memory consumption.
Fine-grained swapping. We will develop a capability-based swapping mechanism operating at byte-level granularity, maximising memory and CPU-cycle savings relative to traditional page-granular approaches.
Each contribution should be evaluated against a conventional MMU-based Linux baseline using real data-centre and agentic AI benchmarks, assessing performance, resource savings, security (isolation and attack surface), and compatibility with unmodified applications.
This is systems research with a direct path to industry impact: the project is carried out in collaboration with Unikraft Incorporated, a cloud industry leader in resource-efficient data-centre infrastructure, and prototype MMU-less capability hardware is already available, so work can start immediately.
We are looking for a highly motivated candidate with:
- A strong background in operating systems, computer architecture, or systems programming (C and/or Rust).
- Experience with, or strong interest in, the Linux kernel, low-level memory management, or hardware/software co-design.
- Curiosity about emerging hardware security features (e.g., capability architectures such as CHERI) and a willingness to work close to the hardware.
- Good analytical and experimental skills, and the ability to communicate research clearly.
Prior experience with kernel development, embedded systems, or hardware security is a strong plus, but not required.
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Summary
PhD opportunity to develop a lightweight OS for data-centre workloads on emerging hardware. Focus on resource efficiency, security, and compatibility. Ideal for candidates with systems programming and OS experience.
PhD Opportunity: Resource-Efficient Execution of Data Centre-Grade Workloads with Lightweight Operating Systems on Emerging Capability Hardware
Full-time
The University of Manchester
Manchester, GB
PhD opportunity to develop a lightweight OS for data-centre workloads on emerging hardware. Focus on resource efficiency, security, and compatibility. Ideal for candidates with systems programming and OS experience.
Modern data-centre workloads (e.g., agentic AI) demand strong security guarantees and high performance, which come today at a high resource cost: data-centre hardware and software infrastructures exhibit significant memory footprints and use large amounts of CPU cycles and energy. This trade-off is untenable: the environmental impact of computing is rising, energy and hardware costs are climbing, and the industry urgently needs computer systems that are more frugal without sacrificing security and performance.
The goal of this PhD is to design and implement a lightweight operating system (OS) capable of running modern data-centre workloads on emerging minimal hardware. The solution should 1) cut resource consumption relative to traditional approaches; 2) improve security by strengthening isolation guarantees; 3) match or exceed the performance of conventional solutions; and 4) remain transparently compatible with existing workloads.
Minimal, MMU-less (without a Memory Management Unit) hardware is attractive for resource efficiency and performance. Although historically confined to small embedded devices, such hardware has recently gained capability-based architectural extensions that remove the security barriers previously excluding it from running data-centre workloads. However, combining capabilities with the absence of an MMU introduces significant compatibility challenges: the OS’s isolation model and memory management must be reworked to recover key functionalities normally provided by MMU hardware. The project should extend NoMMU Linux by bringing back these crucial functionalities in the form of three contributions:
Process duplication. Building on our prior work enabling fast, lightweight duplication within a single virtual address space, we will construct a NoMMU Linux-based OS that leverages the target hardware’s capability features to restore transparent copy-on-write process duplication within a single physical address space.
Memory allocation and compaction. Without an MMU, fragmentation is expected to be a major obstacle to efficient memory use. We will design allocation and compaction algorithms exploiting capability hardware’s pointer-tracking to safely relocate data within a physical address space and optimise memory consumption.
Fine-grained swapping. We will develop a capability-based swapping mechanism operating at byte-level granularity, maximising memory and CPU-cycle savings relative to traditional page-granular approaches.
Each contribution should be evaluated against a conventional MMU-based Linux baseline using real data-centre and agentic AI benchmarks, assessing performance, resource savings, security (isolation and attack surface), and compatibility with unmodified applications.
This is systems research with a direct path to industry impact: the project is carried out in collaboration with Unikraft Incorporated, a cloud industry leader in resource-efficient data-centre infrastructure, and prototype MMU-less capability hardware is already available, so work can start immediately.
We are looking for a highly motivated candidate with:
- A strong background in operating systems, computer architecture, or systems programming (C and/or Rust).
- Experience with, or strong interest in, the Linux kernel, low-level memory management, or hardware/software co-design.
- Curiosity about emerging hardware security features (e.g., capability architectures such as CHERI) and a willingness to work close to the hardware.
- Good analytical and experimental skills, and the ability to communicate research clearly.
Prior experience with kernel development, embedded systems, or hardware security is a strong plus, but not required.
The HiPEAC project has received funding from the European Union's Horizon Europe research and innovation funding programme under grant agreement number 101296676. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.
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PhD Opportunity: Resource-Efficient Execution of Data Centre-Grade Workloads with Lightweight Operating Systems on Emerging Capability Hardware in Manchester employer: HiPEAC
KRAI is an exceptional employer located in the heart of Cambridge, UK, where innovation thrives in the vibrant tech hub known as Silicon Fen. We foster a collaborative and dynamic work culture that encourages creativity and professional growth, offering our engineers the opportunity to work on cutting-edge projects that push the boundaries of AI technology. With a commitment to open-source contributions and a track record of excellence in industry competitions, we provide a unique environment for those looking to make a meaningful impact in the field of accelerator programming.
