Julian Höfer, M.Sc.
- Wissenschaftlicher Mitarbeiter
- Gruppe: Prof. Becker
- Raum: 217
CS 30.10 - Tel.: +49 721 608-41310
- julian hoefer ∂does-not-exist.kit edu
- Engesserstr. 5
76131 Karlsruhe
Absicherung von KI-Methoden und Beschleunigern im sicherheitskritischen Umfeld
Die Grundlage für autonomes Fahren und weitere sicherheitskritische Anwendungen ist die zuverlässige Erkennung der unmittelbaren Umgebung mithilfe von Kameras, sowie Radar- und Lidarsensoren. Die besten Ergebnisse zur Objekterkennung liefert hier maschinelles Lernen, z.B. Convolutional Neural Networks. Die Herausforderung besteht akut darin, diese neuronalen Netze in eingebettete Systeme zu integrieren und dabei die Zuverlässigkeit sicherzustellen. Insbesondere zufällige Hardwarefehler sowie die Unfähigkeit, die eigene Unsicherheit zu schätzen, verhindern noch den sicherheitskritischen Einsatz.
KI-Akzelerator – Algorithmus Co-Design und Entwurfsraumexploration
Mit der wachsenden Zahl an Einsatzmöglichkeiten für maschinelles Lernen steigen nicht nur die Anforderungen im Hinblick auf algorithmische Genauigkeit, sondern auch im Hinblick auf die Implementierung in die Hardware. Wichtige Ziele sind die Minimierung des Speicherbedarfs und die Reduktion des Energieverbrauchs. Optimierungen sind hierbei auf algorithmischer Ebene, als auch auf Hardwarearchitekturebene möglich und müssen gegenseitig für die jeweilige Anwendung abgewogen werden. Hierbei erzielen Co-Design Methoden und die zielgerichtete Exploration des Entwurfsraums die besten Ergebnisse.
Energieeffiziente KI-Hardwarebeschleuniger
Maschinelles Lernen kann heutzutage bereits komplexe Probleme in Bildverarbeitung für autonomes Fahren, Industrieautomatisierung oder Fehlererkennung gut lösen. Ein Nachteil solcher Systeme bleibt nach wie vor der hohe Rechenaufwand und damit verbundene Energiebedarf. Aus diesem Grund werden sowohl in der Forschung, als auch in der Industrie (Google, Tesla, …) spezielle Hardwarearchitekturen entwickelt, um die Algorithmen effizient zu implementieren. Auch wir arbeiten im Team an neuen Konzepten und Ideen der Hardwarebeschleunigung im Bereich des maschinellen Lernens.
| LVNr. | Titel | Typ | Semester |
|---|---|---|---|
| 2311617 | Übungen zu 2311615 Digitaltechnik / Grundlagen der Digitaltechnik | Übung (Ü) | WS 24/25 |
| 2311170 | Tutorien zu 2311615 Digitaltechnik / Grundlagen der Digitaltechnik | Tutorium (Tu) | WS 23/24 |
| Titel | Typ |
|---|---|
| Safe and Robust Machine Learning - Application- / Co-Design Perspective | Bachelor-/ Masterarbeit |
| Safe and Robust Machine Learning - Hardware Perspective | Bachelor-/ Masterarbeit |
Betreute studentische Arbeiten (Auswahl)
- BA: „Robustness of Systolic Arrays in Regards to Partial Failures of Computation Units“
- MA: „Modelling and Simulation of Built-in self-test Concepts for Hardware Defect Detection on AI Accelerators“
- BA: „Evaluation of Methods for Sampling-based Uncertainty Estimation in Deep Learning-based Object Detection“
Publikationen
A Dynamically Pipelined Dataflow Architecture for Graph Convolutions in Real-Time Event Interpretation
Neu, M.; Karle, C.; Schmidt, P.; Höfer, J.; Harbaum, T.; Becker, J.
2024. IEEE 37th International System-on-Chip Conference (SOCC 2024), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC62300.2024.10737798
Neu, M.; Karle, C.; Schmidt, P.; Höfer, J.; Harbaum, T.; Becker, J.
2024. IEEE 37th International System-on-Chip Conference (SOCC 2024), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC62300.2024.10737798
LOTTA: An FPGA-based Low-Power Temporal Convolutional Network Hardware Accelerator
Kreß, F.; Serdyuk, A.; Kobsar, D.; Hotfilter, T.; Höfer, J.; Harbaum, T.; Becker, J.
2024. 2024 IEEE 37th International System-on-Chip Conference (SOCC), Dresden, Germany, 16-19 September 2024, 126–131, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC62300.2024.10737863
Kreß, F.; Serdyuk, A.; Kobsar, D.; Hotfilter, T.; Höfer, J.; Harbaum, T.; Becker, J.
2024. 2024 IEEE 37th International System-on-Chip Conference (SOCC), Dresden, Germany, 16-19 September 2024, 126–131, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC62300.2024.10737863
Automated Deep Neural Network Inference Partitioning for Distributed Embedded Systems
Kreß, F.; El Annabi, E. M.; Hotfilter, T.; Hoefer, J.; Harbaum, T.; Becker, J.
2024. 2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 1st-3rd July 2024, Knoxville, 39–44, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISVLSI61997.2024.00019
Kreß, F.; El Annabi, E. M.; Hotfilter, T.; Hoefer, J.; Harbaum, T.; Becker, J.
2024. 2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 1st-3rd July 2024, Knoxville, 39–44, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISVLSI61997.2024.00019
A Challenge-Based Blended Learning Approach for an Introductory Digital Circuits and Systems Course
Hoefer, J.; Gauß, M.; Adams, M.; Kreß, F.; Kempf, F.; Karle, C.; Harbaum, T.; Barth, A.; Becker, J.
2024. 2024 IEEE International Symposium on Circuits and Systems (ISCAS), Singapore, Singapore, 19-22 May 2024, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISCAS58744.2024.10557955
Hoefer, J.; Gauß, M.; Adams, M.; Kreß, F.; Kempf, F.; Karle, C.; Harbaum, T.; Barth, A.; Becker, J.
2024. 2024 IEEE International Symposium on Circuits and Systems (ISCAS), Singapore, Singapore, 19-22 May 2024, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISCAS58744.2024.10557955
EFFECT: An End-to-End Framework for Evaluating Strategies for Parallel AI Anomaly Detection
Stammler, M.; Höfer, J.; Kraus, D.; Schmidt, P.; Hotfilter, T.; Harbaum, T.; Becker, J.
2023. Procedia Computer Science, 222, 499 – 508. doi:10.1016/j.procs.2023.08.188
Stammler, M.; Höfer, J.; Kraus, D.; Schmidt, P.; Hotfilter, T.; Harbaum, T.; Becker, J.
2023. Procedia Computer Science, 222, 499 – 508. doi:10.1016/j.procs.2023.08.188
CNNParted: An open source framework for efficient Convolutional Neural Network inference partitioning in embedded systems
Kreß, F.; Sidorenko, V.; Schmidt, P.; Hoefer, J.; Hotfilter, T.; Walter, I.; Harbaum, T.; Becker, J.
2023. Computer Networks, 229, Article no: 109759. doi:10.1016/j.comnet.2023.109759
Kreß, F.; Sidorenko, V.; Schmidt, P.; Hoefer, J.; Hotfilter, T.; Walter, I.; Harbaum, T.; Becker, J.
2023. Computer Networks, 229, Article no: 109759. doi:10.1016/j.comnet.2023.109759
The ZuSE-KI-Mobil AI Accelerator SoC: Overview and a Functional Safety Perspective
Kempf, F.; Hoefer, J.; Harbaum, T.; Becker, J.; Fasfous, N.; Frickenstein, A.; Voegel, H.-J.; Friedrich, S.; Wittig, R.; Matúš, E.; Fettweis, G.; Lueders, M.; Blume, H.; Benndorf, J.; Grantz, D.; Zeller, M.; Engelke, D.; Eickel, K.-H.
2023. 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), Antwerp, Belgium, 17-19 April 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/DATE56975.2023.10137257
Kempf, F.; Hoefer, J.; Harbaum, T.; Becker, J.; Fasfous, N.; Frickenstein, A.; Voegel, H.-J.; Friedrich, S.; Wittig, R.; Matúš, E.; Fettweis, G.; Lueders, M.; Blume, H.; Benndorf, J.; Grantz, D.; Zeller, M.; Engelke, D.; Eickel, K.-H.
2023. 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), Antwerp, Belgium, 17-19 April 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/DATE56975.2023.10137257
ATLAS: An Approximate Time-Series LSTM Accelerator for Low-Power IoT Applications
Kreß, F.; Serdyuk, A.; Hiegle, M.; Waldmann, D.; Hotfilter, T.; Hoefer, J.; Hamann, T.; Barth, J.; Kämpf, P.; Harbaum, T.; Becker, J.
2023. 26th Euromicro Conference on Digital System Design (DSD 2023), 569–576, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DSD60849.2023.00084
Kreß, F.; Serdyuk, A.; Hiegle, M.; Waldmann, D.; Hotfilter, T.; Hoefer, J.; Hamann, T.; Barth, J.; Kämpf, P.; Harbaum, T.; Becker, J.
2023. 26th Euromicro Conference on Digital System Design (DSD 2023), 569–576, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DSD60849.2023.00084
A Low-Stall Methodology for an Interleaved Processor State Replication
Kempf, F.; Höfer, J.; Hotfilter, T.; Becker, J.
2023. 2023 IEEE 16th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), 276 – 283, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MCSoC60832.2023.00048
Kempf, F.; Höfer, J.; Hotfilter, T.; Becker, J.
2023. 2023 IEEE 16th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), 276 – 283, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MCSoC60832.2023.00048
Leveraging Mixed-Precision CNN Inference for Increased Robustness and Energy Efficiency
Hotfilter, T.; Hoefer, J.; Merz, P.; Kreß, F.; Kempf, F.; Harbaum, T.; Becker, J.
2023. 2023 IEEE 36th International System-on-Chip Conference (SOCC), Santa Clara, USA, 05-08 September 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC58585.2023.10256738
Hotfilter, T.; Hoefer, J.; Merz, P.; Kreß, F.; Kempf, F.; Harbaum, T.; Becker, J.
2023. 2023 IEEE 36th International System-on-Chip Conference (SOCC), Santa Clara, USA, 05-08 September 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC58585.2023.10256738
A Hardware-Aware Sampling Parameter Search for Efficient Probabilistic Object Detection
Hoefer, J.; Hotfilter, T.; Kreß, F.; Qiu, C.; Harbaum, T.; Becker, J.
2023. Computer Vision Systems – 14th International Conference, ICVS 2023, Vienna, Austria, September 27–29, 2023. Ed.: H. Christensen, 299–309, Springer Nature Switzerland. doi:10.1007/978-3-031-44137-0_25
Hoefer, J.; Hotfilter, T.; Kreß, F.; Qiu, C.; Harbaum, T.; Becker, J.
2023. Computer Vision Systems – 14th International Conference, ICVS 2023, Vienna, Austria, September 27–29, 2023. Ed.: H. Christensen, 299–309, Springer Nature Switzerland. doi:10.1007/978-3-031-44137-0_25
A Hardware-Centric Approach to Increase and Prune Regular Activation Sparsity in CNNs
Hotfilter, T.; Höfer, J.; Kreß, F.; Kempf, F.; Kraft, L.; Harbaum, T.; Becker, J.
2023. 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/AICAS57966.2023.10168566
Hotfilter, T.; Höfer, J.; Kreß, F.; Kempf, F.; Kraft, L.; Harbaum, T.; Becker, J.
2023. 2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/AICAS57966.2023.10168566
SiFI-AI: A Fast and Flexible RTL Fault Simulation Framework Tailored for AI Models and Accelerators
Hoefer, J.; Kempf, F.; Hotfilter, T.; Kreß, F.; Harbaum, T.; Becker, J.
2023. Proceedings of the Great Lakes Symposium on VLSI 2023, 287–292, Association for Computing Machinery (ACM). doi:10.1145/3583781.3590226
Hoefer, J.; Kempf, F.; Hotfilter, T.; Kreß, F.; Harbaum, T.; Becker, J.
2023. Proceedings of the Great Lakes Symposium on VLSI 2023, 287–292, Association for Computing Machinery (ACM). doi:10.1145/3583781.3590226
An Analytical Model of Configurable Systolic Arrays to find the Best-Fitting Accelerator for a given DNN Workload
Hotfilter, T.; Schmidt, P.; Höfer, J.; Kreß, F.; Harbaum, T.; Becker, J.
2023. DroneSE and RAPIDO: System Engineering for constrained embedded systems, 73–78, Association for Computing Machinery (ACM). doi:10.1145/3579170.3579258
Hotfilter, T.; Schmidt, P.; Höfer, J.; Kreß, F.; Harbaum, T.; Becker, J.
2023. DroneSE and RAPIDO: System Engineering for constrained embedded systems, 73–78, Association for Computing Machinery (ACM). doi:10.1145/3579170.3579258
Automated Search for Deep Neural Network Inference Partitioning on Embedded FPGA
Kreß, F.; Hoefer, J.; Hotfilter, T.; Walter, I.; El Annabi, E. M.; Harbaum, T.; Becker, J.
2023. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Hrsg.: I. Koprinska. Pt. 1, 557–568, Springer International Publishing. doi:10.1007/978-3-031-23618-1_37
Kreß, F.; Hoefer, J.; Hotfilter, T.; Walter, I.; El Annabi, E. M.; Harbaum, T.; Becker, J.
2023. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Hrsg.: I. Koprinska. Pt. 1, 557–568, Springer International Publishing. doi:10.1007/978-3-031-23618-1_37
Runtime Adaptive Cache Checkpointing for RISC Multi-Core Processors
Kempf, F.; Höfer, J.; Kreß, F.; Hotfilter, T.; Harbaum, T.; Becker, J.
2022. Conference Proceedings: 2022 IEEE 35th International System-on-Chip Conference (SOCC) Ed.: S. Sezer, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC56010.2022.9908110
Kempf, F.; Höfer, J.; Kreß, F.; Hotfilter, T.; Harbaum, T.; Becker, J.
2022. Conference Proceedings: 2022 IEEE 35th International System-on-Chip Conference (SOCC) Ed.: S. Sezer, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC56010.2022.9908110
Hardware-aware Partitioning of Convolutional Neural Network Inference for Embedded AI Applications
Kreß, F.; Hoefer, J.; Hotfilter, T.; Walter, I.; Sidorenko, V.; Harbaum, T.; Becker, J.
2022. 18th International Conference on Distributed Computing in Sensor Systems (DCOSS), 133–140, IEEEXplore. doi:10.1109/DCOSS54816.2022.00034
Kreß, F.; Hoefer, J.; Hotfilter, T.; Walter, I.; Sidorenko, V.; Harbaum, T.; Becker, J.
2022. 18th International Conference on Distributed Computing in Sensor Systems (DCOSS), 133–140, IEEEXplore. doi:10.1109/DCOSS54816.2022.00034
Hardware-aware Workload Distribution for AI-based Online Handwriting Recognition in a Sensor Pen
Kreß, F.; Serdyuk, A.; Hotfilter, T.; Höfer, J.; Harbaum, T.; Becker, J.; Hamann, T.
2022. 2022 11th Mediterranean Conference on Embedded Computing (MECO). Ed.: IEEE, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MECO55406.2022.9797131
Kreß, F.; Serdyuk, A.; Hotfilter, T.; Höfer, J.; Harbaum, T.; Becker, J.; Hamann, T.
2022. 2022 11th Mediterranean Conference on Embedded Computing (MECO). Ed.: IEEE, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/MECO55406.2022.9797131
AnaCoNGA: Analytical HW-CNN Co-Design Using Nested Genetic Algorithms
Fasfous, N.; Vemparala, M. R.; Frickenstein, A.; Valpreda, E.; Salihu, D.; Höfer, J.; Singh, A.; Nagaraja, N.-S.; Voegel, H.-J.; Vu Doan, N. A.; Martina, M.; Becker, J.; Stechele, W.
2022. Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE 2022). Ed.: C. Bolchini, 238–243, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/DATE54114.2022.9774574
Fasfous, N.; Vemparala, M. R.; Frickenstein, A.; Valpreda, E.; Salihu, D.; Höfer, J.; Singh, A.; Nagaraja, N.-S.; Voegel, H.-J.; Vu Doan, N. A.; Martina, M.; Becker, J.; Stechele, W.
2022. Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE 2022). Ed.: C. Bolchini, 238–243, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/DATE54114.2022.9774574
Embedded Face Recognition for Personalized Services in the Assistive Robotics
Walter, I.; Ney, J.; Hotfilter, T.; Rybalkin, V.; Hoefer, J.; Wehn, N.; Becker, J.
2022. Machine Learning and Principles and Practice of Knowledge Discovery in Databases – International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Ed.: M. Kamp, 339–350, Springer International Publishing. doi:10.1007/978-3-030-93736-2_26
Walter, I.; Ney, J.; Hotfilter, T.; Rybalkin, V.; Hoefer, J.; Wehn, N.; Becker, J.
2022. Machine Learning and Principles and Practice of Knowledge Discovery in Databases – International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Ed.: M. Kamp, 339–350, Springer International Publishing. doi:10.1007/978-3-030-93736-2_26
FLECSim-SoC: A Flexible End-to-End Co-Design Simulation Framework for System on Chips
Hotfilter, T.; Hoefer, J.; Kreß, F.; Kempf, F.; Becker, J.
2021. IEEE 34th International System-on-Chip Conference (SOCC), 14th-17th September 2021, Las Vegas, Nevada, USA, 83–88, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC52499.2021.9739212
Hotfilter, T.; Hoefer, J.; Kreß, F.; Kempf, F.; Becker, J.
2021. IEEE 34th International System-on-Chip Conference (SOCC), 14th-17th September 2021, Las Vegas, Nevada, USA, 83–88, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SOCC52499.2021.9739212
Binary-LoRAX: Low-Latency Runtime Adaptable XNOR Classifier for Semi-Autonomous Grasping with Prosthetic Hands
Fasfous, N.; Vemparala, M.-R.; Frickenstein, A.; Badawy, M.; Hundhausen, F.; Höfer, J.; Nagaraja, N.-S.; Unger, C.; Vögel, H.-J.; Becker, J.; Asfour, T.; Stechele, W.
2021. 2021 IEEE International Conference on Robotics and Automation (ICRA): 30 May – 5 June 2021, Xi’an, China, 13430–13437, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRA48506.2021.9561045
Fasfous, N.; Vemparala, M.-R.; Frickenstein, A.; Badawy, M.; Hundhausen, F.; Höfer, J.; Nagaraja, N.-S.; Unger, C.; Vögel, H.-J.; Becker, J.; Asfour, T.; Stechele, W.
2021. 2021 IEEE International Conference on Robotics and Automation (ICRA): 30 May – 5 June 2021, Xi’an, China, 13430–13437, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRA48506.2021.9561045