Fabian Kreß, M. Sc.
- Wissenschaftlicher Mitarbeiter
- group: Prof. Becker
- room: 125.1
CS 30.10 - phone: +49 721 608-41313
- fabian kressXut9∂kit edu
Engesserstr. 5
76131 Karlsruhe
Design Space Exploration for Embedded AI Applications
Today, applications such as object detection or classification in the field of autonomous driving are usually realized by using Artificial Intelligence (AI). In contrast to conventional algorithms, AI can often provide more precise and reliable results. However, AI-based applications usually require to process a huge amount of operations. In the context of embedded platforms, it is therefore important to investigate, how latency, data throughput and power consumption of the system can be optimized considering the constraints imposed by the application.
Emerging Non-Volatile Memory Technologies
In recent decades, novel Non-Volatile Memory technologies (NVMs), such as MRAM or ReRAM, have been introduced and developed further. Emerging NVMs in general consume less static power than SRAM or DRAM and require only a fraction of the area compared to an SRAM cell. Additionally, these technologies enable efficient In-Memory Computing to accelerate matrix-vector multiplications, for example. Therefore, NVMs offer the opportunity to rethink established memory hierarchies and computer architectures for future systems.
Design Space Exploration for Embedded AI Applications
Today, applications such as object detection or classification in the field of autonomous driving are usually realized by using Artificial Intelligence (AI). In contrast to conventional algorithms, AI can often provide more precise and reliable results. However, AI-based applications usually require to process a huge amount of operations. In the context of embedded platforms, it is therefore important to investigate, how latency, data throughput and power consumption of the system can be optimized considering the constraints imposed by the application.
Supervised student works (selection)
- SA: “Emerging Memory Technologies and their use in new System Architectures”
Publications
Lesniak, F.; Kreß, F.; Becker, J.
2021. Applied Reconfigurable Computing. Ed.: S. Derrien, 221–231, Springer Nature Switzerland AG. doi:10.1007/978-3-030-79025-7_15
Masing, L.; Srivatsa, A.; Kreß, F.; Anantharajaiah, N.; Herkersdorf, A.; Becker, J.
2018. IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), Hanoi, VN, September 12-14, 2018, 138–145, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MCSoC2018.2018.00033
Masing, L.; Srivatsa, A.; Kreß, F.; Anantharajaiah, N.; Herkersdorf, A.; Becker, J.
2018. 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC 2018), Hanoi, Vietnam, September 12–14, 2018