Oliver Lenke, M.Sc.
Wissenschaftlicher Mitarbeiter
Technische Universität München
TUM School of Computation, Information and Technology
Lehrstuhl für Integrierte Systeme
Arcisstr. 21
80333 München
Tel.: +49.89.289.28387
Fax: +49.89.289.28323
Gebäude: N1 (Theresienstr. 90)
Raum: N2114
Email: o.lenke@tum.de
Lebenslauf
- Seit 2020 Doktorand am LIS
- 2018-2020 Werkstudent am LIS
- 2018-2020 Master EI (TUM)
- 2015-2018 Bachelor EI (TUM)
- 2016-2019 Tutor für u.a. Werkstoffe der Elektrotechnik, Regelungssysteme, ...
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FPGA System Extension with Encryption and Multicore Support
Beschreibung
As part of this working student position, an existing FPGA-based system architecture and its associated synthesis and configuration toolchain will be extended. The goal is to enhance the platform’s functionality and flexibility by integrating additional hardware components and improving multicore support.
One focus of this work is the integration of an already developed encryption unit into the existing data path architecture. The unit will be placed between the preload unit and the memory controller, enabling transparent encryption and decryption of memory accesses. In addition to the hardware integration itself, the synthesis toolchain must be adapted to properly include and configure the new component within the build process.
A second focus is the extension of the synthesis workflow to support all four instantiated CVA6 cores. The objective is to establish a consistent multicore workflow, including build process adjustments, memory initialization, and program deployment across all cores. As part of this task, a simple demonstration application should be developed that runs on all cores in parallel (e.g., a minimal “Hello World” program without shared variables) to validate correct system behavior.
The tasks include both hardware-related work (such as RTL-level integration and interface adaptation) and activities in the area of build and synthesis automation. The overall goal is to establish a stable and reproducible workflow that seamlessly integrates the new components into the existing infrastructure.
Voraussetzungen
- Good Knowledge about MPSoCs
- Good C programming skills
- Very good VHDL programming skills
- High motivation
- Self-responsible workstyle
Kontakt
Oliver Lenke
o.lenke@tum.de
Betreuer:
Student
Entwicklung und Integration eines 1G-Ethernet-Streaming-Moduls für FPGA-basierte Performance-Analyse
Beschreibung
Im Rahmen dieser Forschungspraxis soll ein Ethernet-basiertes Kommunikationsmodul zur effizienten Übertragung von Laufzeit- und Performance-Daten aus einem FPGA-System entwickelt und integriert werden. Ziel ist es, einen bestehenden Hardware-Prototyp um eine leistungsfähige, nicht-intrusive Streaming-Schnittstelle zu erweitern, die eine kontinuierliche Analyse des Systemverhaltens während der Ausführung ermöglicht.
Kern der Arbeit ist die Integration eines 1G-Ethernet IP-Cores in das FPGA-Board Xilinx VCU118. Aufbauend darauf soll eine stabile Punkt-zu-Punkt-Verbindung zwischen dem FPGA und einem Host-PC realisiert werden. Die Datenübertragung erfolgt paketbasiert über Ethernet und dient der Ausleitung von Metriken, die innerhalb des Systems generiert werden.
Die zu übertragenden Daten bestehen aus einer Menge konfigurierbarer Performance-Metriken mit unterschiedlicher Bitbreite. Diese werden über eine FIFO-Schnittstelle an das Ethernet-Modul übergeben. Als Datenquellen dienen dabei sowohl eine AXI-basierte Traffic-Analyseeinheit als auch Performance Counter der bestehenden Preload-Unit.
Neben der Hardwareentwicklung umfasst die Arbeit auch die Anpassung und Erweiterung einer bestehenden Python-basierten GUI auf dem Host-PC. Diese dient zur Visualisierung und Analyse der empfangenen Daten in Echtzeit. Die Schnittstelle zwischen Hardware und Software soll dabei so gestaltet werden, dass eine einfache Integration neuer Metriken möglich ist.
Voraussetzungen
- Good Knowledge about MPSoCs
- Good C programming skills
- Very good VHDL programming skills
- High motivation
- Self-responsible workstyle
Kontakt
Oliver Lenke
o.lenke@tum.de
Betreuer:
Student
Generischer AXI-Traffic-Analyser zur Charakterisierung von Speicher- und Buszugriffen in eingebetteten Systemen
Beschreibung
Ziel dieser Bachelorarbeit ist die Konzeption und prototypische Umsetzung eines generischen AXI-Traffic-Analysers, der an beliebigen Stellen eines Systems mit AXI-Interface instanziiert werden kann. Der Analyser soll es ermöglichen, den Datenverkehr auf dem Bus flexibel an unterschiedlichen Beobachtungspunkten zu erfassen und auszuwerten. Damit soll eine wiederverwendbare Hardware-Komponente entstehen, die zur Charakterisierung von Kommunikations- und Speicherzugriffsmustern eingesetzt werden kann.
Neben klassischen Kenngrößen wie Datenrate, Zugriffsrate oder Verhältnis von Lese- und Schreibzugriffen sollen insbesondere weiterführende Metriken zur Beschreibung des Zugriffsverhaltens untersucht und implementiert werden. Dazu gehören unter anderem die Verteilung von Strides zwischen aufeinanderfolgenden Speicherzugriffen, die Stabilität dieser Strides über die Zeit, die Dominanz bzw. Verteilung einzelner Cores oder Initiatoren auf dem Bus sowie die Abschätzung des aktuellen Working Sets, beispielsweise über die Anzahl gleichzeitig genutzter Speicherseiten. Darüber hinaus soll analysiert werden, ob ein beobachtetes System eher konstantes oder stark schwankendes Zugriffsverhalten aufweist.
Der AXI-Traffic-Analyser soll zunächst so ausgelegt werden, dass seine Messdaten über den Bus ausgelesen werden können. Bereits bei der Architektur und Schnittstellendefinition soll jedoch eine spätere Erweiterung hin zu einer non-intrusiven Ethernet-Streaming-Variante berücksichtigt werden. Perspektivisch soll der Analysator somit nicht nur lokal auslesbare Statistiken bereitstellen, sondern auch eine kontinuierliche Übertragung von Messdaten über Ethernet unterstützen, sobald ein entsprechendes Interface im Gesamtsystem verfügbar ist.
Im Rahmen der Arbeit sollen die Anforderungen an einen solchen Analysator definiert, eine Hardware-Architektur entworfen und ein erster Prototyp implementiert sowie beispielhaft evaluiert werden.
Voraussetzungen
- Good Knowledge about MPSoCs
- Good C programming skills
- Very good VHDL programming skills
- High motivation
- Self-responsible workstyle
Kontakt
Oliver Lenke
o.lenke@tum.de
Betreuer:
Student
Evaluation of a Page-Based Memory Preload Architecture Using Standardized Embedded Benchmarks
Beschreibung
Modern MPSoC architectures are increasingly limited by off-chip memory latency. To mitigate this bottleneck, a page-based hardware preload unit has been developed that speculatively transfers DRAM pages upon last-level cache misses in order to hide memory access latency.
The goal of this bachelor thesis is to perform a systematic and scientifically sound evaluation of this architecture using internationally recognized embedded benchmark suites. The work will focus on identifying, porting, and executing suitable bare-metal benchmarks on an FPGA-based RISC-V platform (CVA6 architecture). Candidate benchmark suites include Embench, CoreMark, PolyBench/C, MiBench, and other memory-intensive workloads. The final selection will be made during the course of the thesis based on feasibility and relevance.
The thesis involves implementing the benchmarks in the existing hardware/software framework, conducting structured performance measurements, and comparing different system configurations (e.g., with and without the preload unit). Particular emphasis will be placed on analyzing memory behavior, working-set characteristics, and access patterns.
Beyond implementation, the thesis will provide a scientific evaluation of how different workload classes interact with page-based preloading. Results will be analyzed quantitatively and presented in a clear and reproducible manner using normalized speedups and workload classifications.
The outcome of this work will provide a solid experimental foundation for further research and potential publications in the area of memory-optimized MPSoC architectures.
Voraussetzungen
- Good Knowledge about MPSoCs
- Good C programming skills
- Basic understanding of hardware-oriented programming style
- High motivation
- Self-responsible workstyle
Kontakt
Oliver Lenke
o.lenke@tum.de
Betreuer:
Student
Balancing Preload Efficiency and Responsiveness through Adaptive Burst Lengths
Beschreibung
Page-based memory preloading typically relies on fixed burst lengths to transfer data efficiently from DRAM. While long bursts maximize preload throughput, they reduce responsiveness to demand-driven CPU memory accesses. Short bursts improve reactivity but underutilize available memory bandwidth.
This thesis builds on the existing page-based preload unit and investigates a hardware-based mechanism for dynamically adjusting preload burst length according to current memory system utilization. The goal is to balance preload efficiency and fast reaction to demand accesses at runtime. The proposed mechanism adapts burst length based on simple runtime indicators such as DRAM activity or the presence of competing CPU requests. The implementation extends the existing preload FSM and does not require any modifications to the CPU microarchitecture
Evaluation on an FPGA-based platform analyzes execution time, interference with demand accesses, and bandwidth utilization under different memory-intensive workloads. The results aim to demonstrate that adaptive burst sizing is an effective and low-overhead technique to improve the robustness of memory-side preloading.
Voraussetzungen
- Good Knowledge about MPSoCs
- Good C programming skills
- High motivation
- Self-responsible workstyle
Kontakt
Oliver Lenke
o.lenke@tum.de
Betreuer:
Student
Self-Adaptive Control of Page-Based Preloading
Beschreibung
Hardware preloading mechanisms, as investigated in the current project, must balance latency hiding against bandwidth efficiency. While page-based preloading can effectively amortize memory access latency, it may also lead to unnecessary bandwidth consumption when memory access patterns change dynamically. This thesis builds upon an existing page-based preload unit that incrementally transfers memory pages. The current baseline design employs fixed policies for page switching and preload completion, independent of the observed usefulness of partially loaded pages.
The objective of this work is to enhance the preload unit with self-adaptive control mechanisms that dynamically adjust preloading behavior based on runtime feedback. In particular, the preload unit shall monitor the usefulness of partially preloaded pages, enabling early termination of preload operations when further progress is unlikely to produce additional cache hits. Furthermore, the student will extend the page switching logic to consider multiple factors, including page priority, observed reuse, preload progress, and interruption frequency.
Experimental observations indicate that pages suspended due to page switching are often not accessed again in the future, raising the question under which conditions such pages should remain in the priority queue for continued preloading. In addition, the thesis will investigate more advanced priority strategies that augment the existing temporal and spatial locality scheme with runtime feedback and observed memory behavior.
All proposed strategies shall be developed and evaluated using RTL-based simulation as well as FPGA-based implementations. The overall goal of this thesis is to derive a self-adaptive and enhanced version of the existing preload unit. The enhanced design will be evaluated using synthetic microbenchmarks and representative benchmarks. The evaluation will quantify improvements in bandwidth efficiency and preload effectiveness under varying memory access characteristics.
Voraussetzungen
- Strong Experience with VHDL Coding
- Basic Knowledge is C Programmng
- Basic knowledge on MPSoC, cache hierarchies etc.
Kontakt
Oliver Lenke
o.lenke@tum.de
Betreuer:
Student
Abgeschlossene Arbeiten
Integration of a Hardware Preload Unit into an AXI-based CVA6 Architecture
Working Student Job, Robert Zamora, April 2026
A Tightly LLC-Coupled Spatial-Locality- and History-Aware Memory Preload Unit
Master's Thesis, Martin Münch, March 2026
Development of a Hardware Test Framework for Simulation and FPGA-Based Evaluation
Bachelor's Thesis, Penelope Duntze, March 2026
FPGA-Based Design and Implementation of Dynamic Preloading Features
Bachelor's Thesis, Kateryna Liudkevich, Feburary 2026
Non-Intrusive Performance Monitoring Framework for a Memory Preloading Module
Master's Thesis, Aleksa Stojkovic, December 2025
Design and Implementation of Dynamic Preloading Features on an FPGA Prototype
Bachelor's Thesis, Theodor Ettling, October 2025
Evaluation Framework for a SystemC-based MPSoC Prototype Architecture
Working Student Job, Mateus Lima, September 2025
Design and Integration of a Hardware Performance Counter Unit for Memory Access Statistics
Bachelor's Thesis, Matteo Calabrò, August 2025
Design of a Prioritization Logic for a Page Preloading Mechanism
Research Practice, Jakob Winterer, July 2025
Integration of a Hardware Preload Unit into an AXI-based CVA6 Architecture
Bachelor's Thesis, Robert Zamora, June 2025
Exploring Optimal Memory Transfer Schedules in Hierarchical Memory Architectures: A Benchmark Study on the Streaming Transfer Controller of the TC4x PPU for Embedded AI Workloads
Master's Thesis, Radhika Rajeev Nair, April 2025, Cooperation with Infineon AG
Analysis and Visualization of Cache Access Behavior in CPU Clusters
Bachelor's Thesis, Klimentij Batenko, March 2025
Analyse von Laufzeit-Statistiken eines SystemCMPSoC-Simulationsmodells mit Python
Bachelor's Thesis, Quynh Thy Laura Vo, March 2025
Evaluation Framework for a SystemC-based MPSoC Prototype Architecture
Bachelor's Thesis, Mateus Lima, Feburary 2025
Memory Access Prioritisation on an FPGA-Based MP-SoC System
Research Practice, Jonathan Ross, Feburary 2025
Development of a C Testsuite for a Memory Preloading Mechanism of an MPSoC
Bachelor's Thesis, Fabian Strasser, December 2024
Fine granular Page Preloading Mechanism on an FPGA Prototype
Research Practice, Aurel Prestel, November 2024
Investigating DMA Transfer Configurations for Optimal Utilization of DDR Memory Bandwidth
Research Practice, Seçkin Gezer, October 2024, Cooperation with WORK Microwave
Design and Implementation of a Stride Prefetching Mechanism in SystemC
Research Practice, Sruthi Haridas, July 2024
Design and Implementation of a Memory Prefetching Mechanism on an FPGA Prototype
Master's Thesis, Christoph Foltyn, June 2024
Interrupt Latency Investigations with YoctoRT and FreeRTOS on Xilinx Versal Evaluation Board
Master's Thesis, Kiran Bhandarkar, April 2024, Cooperation with Rohde&Schwarz
SystemC Model for Memory Preloading
Research Practice, Ali Emre Heybeli, February 2024
An Efficient, Scalable and SIMD-friendly Hybrid FFT Computation Method
Master's Thesis, Jiawen Qi, January 2024, Cooperation with Huawei
SystemC Model for Memory Preloading
Research Practice, Jingyi Liu, December 2023
Lifetime Analysis of Flash Memory Devices in Automotive Use Cases
Bachelor's Thesis, Simon Weigl, July 2023, Cooperation with BMW AG
Automatic Hardening of Registers in Safety Critical Microcontrollers
Bachelor's Thesis, Jonathan Ross, July 2023, Cooperation with Infineon AG
Design and Implementation of a flexible SPI Fault Injection Unit
Bachelor's Thesis, Hannes Matheis, December 2022, Cooperation with Infineon AG
Design and Implementation of a Hardware Accelerator for VSM Page Writeback
Master's Thesis, Thomas Leyk, November 2022, Cooperation with FAU
Scalability Analysis of Hardware Acceleration on Central and Distributed Memory Systems
Master's Thesis, Jens Nöpel, November 2022
Measurement and Analysis of a Tile-based MPSoC System
Research Practice, Gabriel Pempel, November 2022, Cooperation with FAU
Design and Implementation of a HW-based Memory Protection Unit for Tile-based MPSoCs
Master's Thesis, Peter Körner, October 2022, Cooperation with FAU
DYNAMIT: Dynamic Acceleration of Memory-Stores in Tile-based Architectures
Master's Thesis, Michael Geier, August 2022
Laufzeit Vorhersage von Hardwarebeschleuniger und Near-Memory-Computing
Bachelor's Thesis, Sahil Salotra, September 2021
Extending an Utilization Counter Framework for On-Chip AHB Bus Systems
Bachelor's Thesis, Humayra Jeba Binte Mohd Habibur Rahman, July 2021, Cooperation with SIT
Best Thesis Award
Utilization Monitoring and Analysis of a Near-Memory-Computing System
Research Practice, Richard Petri, May 2021
Publikationen
2026
- STEP: Spatial Footprint Prefetcher with Multi-Point Temporal Triggers. The 53rd International Symposium on Computer Architecture (ISCA 2026), 2026 mehr… BibTeX Volltext ( DOI )
2025
2024
2023
- Information Processing Factory 2.0 - Self-awareness for Autonomous Collaborative Systems. DATE 2023, 2023 mehr… BibTeX Volltext ( DOI )
2022
- Invasive NoCs and Memory Hierarchies for Run-Time Adaptive MPSoCs. In: Invasive Computing. FAU University Press, Universitätsstraße 4, 91054 Erlangen, 2022 mehr… BibTeX Volltext ( DOI )
- Validation and Demonstrator. In: Invasive Computing. FAU University Press, Universitätsstraße 4, 91054 Erlangen, 2022 mehr… BibTeX
2021
2020
- X-CEL: A Method to Estimate Near-Memory Acceleration Potential in Tile-based MPSoCs. ARCS 2020 - 33rd International Conference on Architecture of Computing Systems, 2020 mehr… BibTeX
- DySHARQ: Dynamic Software-Defined Hardware-Managed Queues for Tile-Based Architectures. International Journal of Parallel Programming, 2020 mehr… BibTeX Volltext ( DOI )
- X-Centric: A Survey on Compute-, Memory- and Application-Centric Computer Architectures. MEMSYS'20: The International Symposium on Memory Systems , 2020 mehr… BibTeX