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
| First Name | Last Name | Title |
|---|---|---|
| Aldin | Berisa | Doctoral student |
| Ali | Zoljodi | Doctoral student |
| Amin | Majd | |
| Bahar | Houtan | Doctoral student |
| Björn | Lisper | Professor |
| Farnam | Khalili Maybodi | Research Engineer/Technician |
| Håkan | Forsberg | Senior Lecturer |
| Ines | Alvarez | Post Doc |
| Joakim | Lindén | Industrial Doctoral Student |
| Johan | Hjorth | Doctoral student |
| Madiha | Umar | Doctoral student |
| Mahdi | Taheri | Doctoral student |
| Masoud | Daneshtalab | Professor |
| Mehdi | Modarressi | |
| Mikael | Sjödin | Professor,Research Leader |
| Mohammad | Ahmadilivani | Doctoral student |
| Mohammad | Ashjaei | Associate Professor,Docent |
| Mohammad | Riazati | Doctoral student |
| Mostafa | Salehi | |
| Nandinbaatar | Tsog | |
| Saad | Mubeen | Professor |
| Sahar | Mobaiyen | Doctoral student |
| Seyedhamidreza | Mousavi | Doctoral student |
| Sima | Sinaei | Post Doc |
| Somayeh | Abdi | Post Doc |
| Yana | Tejasukmana | Doctoral student |
| Zenepe | Satka | Doctoral student |
Experimental Analysis of Wireless TSN Networks for Real-time Applications (Oct 2023) Zenepe Satka, Deepa Barhia , Sobia Saud , Saad Mubeen, Mohammad Ashjaei 28th International Conference on Emerging Technologies and Factory Automation (ETFA 2023)
Efficient On-device Transfer Learning using Activation Memory Reduction (Sep 2023) Amin Yoosefi , Seyedhamidreza Mousavi, Masoud Daneshtalab, Mehdi Kargahi International Conference on Fog and Mobile Edge Computing (FMEC)
DASS: Differentiable Architecture Search for Sparse Neural Networks (Sep 2023) Seyedhamidreza Mousavi, Mohammad Loni, Mina Alibeigi , Masoud Daneshtalab ACM Transactions on Embedded Computing Systems (TECS 2023)
DASS: Differentiable Architecture Search for Sparse Neural Networks (Sep 2023) Seyedhamidreza Mousavi, Mohammad Loni, Mina Alibeigi , Masoud Daneshtalab EMBEDDED SYSTEMS WEEK (ESWEEK 2023)
Comparative Evaluation of Various Generations of Controller Area Network Based on Timing Analysis (Sep 2023) Aldin Berisa, Mohammad Ashjaei, Masoud Daneshtalab, Mikael Sjödin, Adis Panjevic , Imran Kovac , Hans Lyngbäck , Saad Mubeen 28th International Conference on Emerging Technologies and Factory Automation (ETFA 2023)
Towards Modelling 5G Communication in Software Architectures of Vehicular CPS (Sep 2023) Zenepe Satka, Saad Mubeen, Mohammad Ashjaei, John Lundbäck 49th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA 2023)
