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 |
Håkan | Forsberg | Senior Lecturer |
Inés | Álvarez | Post Doc |
Joakim | Lindén | Industrial Doctoral Student |
Johan | Hjorth | 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 | Loni | Doctoral student |
Mohammad | Riazati | Doctoral student |
Mostafa | Salehi | |
Nandinbaatar | Tsog | |
Saad | Mubeen | Associate Professor,Docent |
Sima | Sinaei | Post Doc |
Zenepe | Satka | Doctoral student |
Towards a Predictable and Cognitive Edge-Cloud Architecture for Industrial Systems (Jul 2022) Mohammad Ashjaei, Saad Mubeen, Masoud Daneshtalab, Victor Casamayor , Geoffrey Nelissen Real-time And intelliGent Edge computing workshop (RAGE2022)
HERMES: Heuristic Multi-queue Scheduler for TSN Time-Triggered Traffic with Zero Reception Jitter Capabilities (Jun 2022) Daniel Bujosa Mateu, Mohammad Ashjaei, Alessandro Papadopoulos, Thomas Nolte, Julián Proenza The 30th International Conference on Real-Time Networks and Systems (RTNS'22)
AVB-aware Routing and Scheduling for Critical Traffic in Time-sensitive Networks with Preemption (Jun 2022) Aldin Berisa, Luxi Zhao , Silviu Craciunas , Mohammad Ashjaei, Saad Mubeen, Masoud Daneshtalab, Mikael Sjödin The 30th International Conference on Real-Time Networks and Systems (RTNS'22)
Schedulability Analysis of WSAN Applications: Outperformance of A Model Checking Approach (May 2022) Ehsan Khamespanah , Morteza Mohaqeqi , Mohammad Ashjaei, Marjan Sirjani
TAS:Ternarized Neural Architecture Search for Resource-Constrained Edge Devices (Mar 2022) Mohammad Loni, Hamid Mousavi , Mohammad Riazati, Masoud Daneshtalab, Mikael Sjödin Design, Automation and Test in Europe Conference (DATE'22)
Communication Patterns in Automotive Systems (Mar 2022) Ruben Broux, Elena Lisova, Saad Mubeen