HYPNOS
Co-Design of Persistent, Energy-efficient and High-speed Embedded Processor Systems with Hybrid Volatility Memory Organisation
This project is funded by the German Research Foundation (DFG) within the Priority Program SPP 2377 "Scalable Data Management for Future Hardware".
HYPNOS explores how emerging non-volatile memory (NVM) technologies could beneficially replace not only main memory in modern embedded processor architectures, but potentially also one or multiple levels of the cache hierarchy or even the registers and how to optimize such a hybrid-volatile memory hierarchy for offering high speed and low energy tradeoffs for a multitude of application programs while providing persistence of data structures and processing state in a simple and efficient way.
On the one hand, completely non-volatile (memory) processors (NVPs) that have emerged for IoT devices are known to suffer from low write times of current NVM technologies as well as by orders of magnitude lower endurance than, e.g., SRAM, thus prohibiting an operation at GHz speeds. On the other hand, existing NVM main memory computer solutions suffer from the need of the programmer to explicitly persist data structures through the cache hierarchy.
HYPNOS (Named after the Greek god of sleep.) systematically attacks this intertwined performance/endurance/programmability gap by taking a hardware/software co-design approach:
Our investigations include techniques for
a) design space exploration of hybrid NVM memory processor architectures} wrt. speed and energy consumption including hybrid (mixed volatile) register and cache-level designs,
b) offering instruction-level persistence for (non-transactional) programs in case of, e.g., instantaneous power failures through low-cost and low-latency control unit (hardware) design of checkpointing and recovery functions, and additionally providing
c) application-programmer (software) persistence control on a multi-core HyPNOS system for user-defined checkpointing and recovery from these and other errors or access conflicts backed by size-limited hardware transactional memory (HTM).
d) The explored processor architecture designs and different types of NVM technologies will be systematically evaluated for achievable speed and energy gains, and for testing co-designed backup and recovery mechanisms, e.g., wakeup latencies, etc., using a gem5-based multi-core simulation platform and using ARM processors with HTM instruction extensions.
As benchmarks, i) simple data structures, ii) sensor (peripheral device) I/O and finally iii) transactional database applications shall be investigated and evaluated.
Publications
2024
- Letras M.:
Techniques for Efficient Performance Analysis and Memory Optimization in Mapping Dataflow Models of Computation onto Embedded Systems (Dissertation, 2024)
DOI: 10.25593/open-fau-1040
URL: https://open.fau.de/handle/openfau/31834
BibTeX: Download - Letras M., Falk J., Teich J.:
Exploring Multi-Reader Buffers and Channel Placement during Dataflow Network Mapping to Heterogeneous Many-core Systems
In: IEEE Access 12 (2024), p. 39748-39769
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3375079
BibTeX: Download - Wilbert N., Wildermann S., Teich J.:
Hybrid Cache Design Under Varying Power Supply Stability - A Comparative Study
10th International Symposium on Memory Systems (Washington, D.C., 30. September 2024 - 3. October 2024)
In: MEMSYS '24: Proceedings of the International Symposium on Memory Systems 2024
DOI: 10.1145/3695794.3695819
BibTeX: Download - Wilbert N., Wildermann S., Teich J.:
To Keep or Not to Keep - The Volatility of Replacement Policy Metadata in Hybrid Caches
2nd Workshop on Disruptive Memory Systems (Austin, TX, 3. November 2024 - 3. November 2024)
In: Proceedings of the 2nd Workshop on Disruptive Memory Systems 2024
DOI: 10.1145/3698783.3699381
BibTeX: Download
2023
- Henkel J., Sidduh L., Bauer L., Teich J., Wildermann S., Tahoori MB., Mayahinia M., Castrillon J., Khan AA., Farzaneh H., de Lima JPC., Chen JJ., Hakert C., Chen KH., Yang CL., Cheng HY.:
Special Session - Non-Volatile Memories: Challenges and Opportunities for Embedded System Architectures with Focus on Machine Learning Applications
International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES) (HAMBURG, 18. September 2023 - 20. September 2023)
In: Proceedings of the International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES) 2023
BibTeX: Download