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.
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|
|Farnam||Khalili Maybodi||Research Engineer/Technician|
|Joakim||Lindén||Industrial Doctoral Student|
|PROVIDENT: Predictable Software Development in Connected Vehicles Utilising Blended TSN-5G Networks||active|
|AutoDeep: Automatic Design of Safe, High-Performance and Compact Deep Learning Models for Autonomous Vehicles||active|
|AutoFL: Cross-Layer Trusted Systems for Heterogeneous Federated Learning at Scale||active|
|Dependable AI in Safe Autonomous Systems||active|
|FASTER-ΑΙ: Fully Autonomous Safety- and Time-critical Embedded Realization of Artificial Intelligence||active|
|GreenDL: Green Deep Learning for Edge Devices||active|
|RELIANT Industrial graduate school: Reliable, Safe and Secure Intelligent Autonomous Systems||active|
|SafeDeep: Dependable Deep Learning for Safety-Critical Airborne Embedded Systems||active|
|SEINE:Automatic Self-configuration of Industrial Networks||active|
|DeepMaker: Deep Learning Accelerator on Commercial Programmable Devices||finished|
|DESTINE: Developing Predictable Vehicle Software Utilizing Time Sensitive Networking||finished|
|Energy-Efficient Hardware Accelerator for Embedded Deep Learning||finished|
|HERO: Heterogeneous systems - software-hardware integration||finished|
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)