Heterogeneous systems - hardware software co-design
Focus:
The group aims to boost exploitation of heterogeneous systems in terms of predictability, effective development and efficient software-hardware integration for next-generation intelligent embedded systems.
webpage: https://www.es.mdh.se/hero/
With the exploding need for high-performance computing, we are at the dawn of the heterogeneous era, where all future computing platforms are likely to embrace heterogeneity. In a heterogeneous system, there can be several different computational units such as multi-core central processing units (CPUs), graphics processing units (GPUs), field-programmable gate arrays (FPGAs), digital signal processing units (DSPs), and artificial intelligence (AI) accelerators/engines.
One major driving force for heterogeneous systems is the next generation intelligent, adaptive and autonomous systems that will form the base for coming products like autonomous vehicles and autonomous manufacturing.
With a diverse range of architectures (on a single chip or distributed), a main challenge is to make use of the enormous computational power in the best way, while still meeting several criteria like performance, energy efficiency, time predictability, and dependability.
The overall goal of this research group is to tackle the following scientific areas:
• Hardware/software co-design and integration
• System architecture and specialization
• AI and deep learning acceleration
• Model-based development of predictable software architectures
• Pre-runtime analysis of heterogeneous embedded systems
Efficient AVB-aware Scheduling for Critical Traffic in Time-sensitive Networks (May 2026) Daniel Bujosa Mateu, Silviu Craciunas , Saad Mubeen 32nd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS2026)
Physics-Informed Recurrent Architecture with Embedded Thermodynamic Dynamics for Robust Sequence Modeling (Apr 2026) Zafer Yigit, Håkan Forsberg, Masoud Daneshtalab 34th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2026)
Architecting Automotive Software for the Emerging Compute-in-the-Network Paradigm (Apr 2026) Saad Mubeen, Mohammad Ashjaei, John Lundbäck 48th IEEE/ACM International Conference on Software Engineering (ICSE 2026)
Traffic-Aware Configuration of OPC UA PubSub in Industrial Automation Networks (Apr 2026) Kasra Ekrad, Bjarne Johansson, Inés Álvarez , Saad Mubeen, Mohammad Ashjaei IEEE International Conference on Industrial Technology (ICIT 2026) (ICIT26)
Bridging TSN and 5G networks: Prototype design and evaluation for real-time embedded systems (Nov 2025) Zenepe Satka, Mohammad Ashjaei, Josefina Nord , William Rosales Mayta , Didrik Nordin , Daniel Ragnarsson , Saad Mubeen Journal of Systems Architecture, 2025 (JSA)
FedLoRASwitch: Efficient Federated Learning via LoRA Expert Hotswapping and Routing (Oct 2025) Joakim Flink, Bostan Khan, Masoud Daneshtalab The 3rd IEEE International Conference on Federated Learning Technologies and Applications (FLTA25)
