Academic Publications

FRACTAL Project: Research Articles

The list of academic publications done during the project for the support and sharing of the FRACTAL technology development.

1. “A 10-core SoC with 20 Fine-Grain Power Domains for Energy-Proportional Data-Parallel Processing over a Wide Voltage and Temperature Range”
Submitted to: Integrated Systems Laboratory (IIS)
Responsible partner: ETH Zurich (ETHZ)
FRACTAL project relevance: Power gating is a well-known technique to reduce leakage power in large System-on-Chips, in this paper, FRACTAL partner ETH Zurich has explored a fine-grained power gating technique with 20 individually controlled power islands that can be turned on and off on demand saving up to 41% power.

2. “EDISON: An Edge-native Method and Architecture for Distributed Interpolation 
Submitted to: Sensors 21, no. 7: 2279. Sensors and Smart Devices at the Edge: IoT Meets Edge Computing.
Responsible partner: University of Oulu (UOULU)
FRACTAL project relevance: In their article, researchers from the University of Oulu present EDISON – a novel edge-native, distributed interpolation architecture for the smart city networking environment. EDISON’s device layer comprises fixed sensors as well as mobile sensors mounted on vehicles. IoT gateways provide connectivity, store mobile sensor observations, and provide local computational capabilities. The edge layer has edge servers and enhances the fixed sensors with connectivity and further computational capacity. Cloud provides coordination and centralized processing. Is part of the academic study on FRACTAL AI.

3. On-Demand Redundancy Grouping: Selectable Soft-Error Tolerance for a Multicore Cluster
Submitted to: ISVLSI2022 (IEEE Computer Society Annual Symposium on VLSI)
Responsible partner: ETH Zurich (ETHZ)
FRACTAL project relevance: With the shrinking of technology nodes and the use of parallel processor clusters in hostile and critical environments, such as space, run-time faults caused by radiation are a serious cross-cutting concern, also impacting architectural design. This paper introduces an architectural approach to run-time config- urable soft-error tolerance at the core level, augmenting a six-core open-source RISC-V cluster with a novel On-Demand Redun- dancy Grouping (ODRG) scheme.

4. “MiniFloat-NN and ExSdotp: An ISA Extension and a Modular Open Hardware Unit for Low-Precision Training on RISC-V Cores”
Submitted to: ARITH conference, Sep12-14 2022
Responsible partner: ETH Zurich (ETHZ)
FRACTAL project relevance: Low-precision formats have recently driven major breakthroughs in neural network (NN) training and inference by reducing the memory footprint of the NN models and improving the energy efficiency of the underlying hardware architectures. Narrow integer data types have been vastly investigated for NN inference and have successfully been pushed to the extreme of ternary and binary representations. In contrast, most training- oriented platforms use at least 16-bit floating-point (FP) formats. Lower-precision data types such as 8-bit FP formats and mixed- precision techniques have only recently been explored in hardware implementations. We present MiniFloat-NN, a RISC-V instruction set architecture extension for low-precision NN training, providing support for two 8-bit and two 16-bit FP formats and expanding op- erations.

5. “Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration”
Submitted to: Proceedings of the IEEE, May 2022
Responsible partner: University of Oulu (UOULU)
FRACTAL project relevance: The main focus of the article is on the AI-based orchestration in the device-edge-cloud computing continuum.

6. “Triggering Conditions Analysis and Methodology for validation of ADAS/AD functions: A use case study”
Presented at: IEEE Inteligent Vehicles Symbosium in Aachen, Germany, at June 5th-9th 2022
Responsible partner: Virtual Vehicle (VIF)
FRACTAL project relevance: Covers safety analysis topics related to UC7 (SPIDER autonomous robot).

7. “Improving the Robustness of Redundant Execution with Register File Randomization”
Presented at: ICCAD conference, November 2021
Responsible partner: Valencia Polytechnic University (UPV)
FRACTAL project relevance: This article proposes RFR, a new technique to increase the robustness of redundant execution in the context of safety-critical applications. RFR randomizes the mapping of processors architectural registers to avoid common cause faults in the FRACTAL-based RISCV computing nodes. It supports project activities on HW support for safety.

8. “Weathering the Reallocation Storm: Large-Scale Analysis of Edge Server Workload”
Presented at: Joint EuCNC & 6G Summit 2021
Responsible partner: Univesity of Oulu (UOULU)
FRACTAL project relevance: The topic of the paper is edge orchestration. In more detail, the article analyses the workloads accumulating on a large deployment of edge servers in a number of scenarios and with different workload reallocation / migration strategies. We identify a phenomenon (named the “reallocation storm”) where a high number of reallocations on the edge network are superfluous, that is, happening unnecessarily. We study the causes behind reallocation storms, and look for ways to avoid them.

9. “The ECSEL FRACTAL Project: A Cognitive Fractal and Secure edge based on a unique Open-Safe-Reliable-Low Power Hardware Platform
Responsible partner: IKERLAN (IKER)
FRACTAL project relevance: This paper has presented the ECSEL FRACTAL project. The aim of the project is to create a reliable computing platform node, realizing a so-called Cognitive Edge under industry standards. The project builds on knowledge of partners gained in current or former EU projects and will demonstrate the newly conceived approaches to co-engineering across use cases spanning Transport and Industrial Control. As the paper is written at the beginning of the project, it focuses rather on the project introduction.

10. “Research and Education Towards Smart and Sustainable World”
Responsible partner: University of Oulu (UOULU)
FRACTAL project relevance: This paper proposes a vision for directing research and education in the field of information and communications technology (ICT). Our Smart and Sustainable World vision targets prosperity for the people and the planet through better awareness and control of both human-made and natural environments. The needs of society, individuals, and industries are fulfilled with intelligent systems that sense their environment, make proactive decisions on actions advancing their goals, and perform the actions on the environment.

11. “Time-Triggered Frequency Scaling in Network-on-Chip for Safety-Relevant Embedded Systems”
Responsible partner: University of Siegen (SIEGEN)
FRACTAL project relevance: Networks on Chip (NoC) are used in Multiprocessor System on a Chip (MPSoC) architectures and safety-relevant systems as a communication backbone to cope with high communication traffic. Nevertheless, network interfaces and the routers within the NoC add to the power consumed by the chip. This paper presents models and algorithms for low power techniques in NoC based on dynamic frequency scaling for safety-relevant real-time systems.

12. “Extension of the LISNoC (Network -on-chip) with an AXI”
Responsible partner: University of Siegen (SIEGEN)
FRACTAL project relevance: Over the years, Network-on-Chip (NoC) has under-gone a rapid evolution which urges the performance of NoCs to be analyzed thoroughly. Several NoC solutions exist, but the performance of these NoCs are tied to application requirements. Therefore, it has become practical to extend existing NoCs to satisfy particular application requirements. The LISNoC is one such NoCs that is open-source and provides an easily adaptable implementation to extend its features to satisfy different application requirements. Mainly, this work extends the LISNoC to support source-based routing and equips the LISNoC with a new AXI-based network interface.

13. “Adaptive Scheduling for Time-Triggered Network-on-Chip-Based Multi-Core Architecture Using Genetic Algorithm”
Responsible partner: University of Siegen (SIEGEN)
FRACTAL project relevance: In this work, an algorithm for path reconvergence in a multi-schedule graph, enabled by a reconvergence horizon, is presented to manage the state-space explosion problem resulting from an increase in the number of scenarios required for adaptation.

14. “AI-Based Scheduling for Adaptive Time-Triggered Networks”
Presented at: MECO2022 & CPSIoT 2022
Responsible partner: University of Siegen
FRACTAL project relevance: Time-triggered systems are ideal for safety-critical systems due to the inherent determinism and better fault tolerance. However, the current trend of adaptation in time-triggered systems is typically limited to switching between a small number of precomputed schedules. Artificial neural networks (ANNs) have the potential to overcome this limitation. In this paper, an ANN is implemented to learn schedules to provide adaptation for time-triggered systems while ensuring that collision and precedence constraints are met. In our evaluation, the AI-based scheduler is compared with conventional scheduling algorithms such as list scheduling and genetic algorithm in terms of makespan and computation time. The results show the AI-based scheduler’s potential when increasing the scheduling problem’s complexity.

15. “Deep Learning based Meta-scheduling in real time systems”
Presented at: 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)
Responsible partner: University of Siegen (SIEGEN)
FRACTAL project relevance: TBA 

16. “Ternarized TCN for μJ/Inference Gesture Recognition from DVS Event Frames”
Presented at: Design Automation and Test in Europe (DATE 2022)
Responsible partner: ETH Zurich
FRACTAL project relevance: To be presented.

17. “Systematic Prevention of On-Core Timing Channels by Full Temporal Partitioning
Presented at: IEEE Transcactions on Computers, 2022
Responsible partner: ETH Zurich
FRACTAL project relevance: TBA

18. “Leveraging the PULP Platform to Build Reliable Systems
Presented at: HIPEAC 2022
Responsible partner: ETH Zurich
FRACTAL project relevance: PULP platform is used and validated for different use case and system applications within the project.

19. Spatial dependency in Edge-native Artificial Intelligence
Presented at: doctoral dissertation presented in L3, Linnanmaa, on 12 November 2021
Responsible partner: University of Oulu (UOULU)
FRACTAL project relevance: This thesis studies edge AI – an important part of work in the project, needed to deliver the knowledge for building the FRACTAL system. A nascent field of research combining edge computing and artificial intelligence. A particular focus in the thesis is on spatial dependencies, which quantify the similarity of observations in the spatial dimension. Spatial dependencies are prominent in edge AI due to the local nature of edge service users, the computational resources, as well as many of the observed data-generating processes.

20. “Situation Awareness for Autonomous Vehicles Using Blockchain-Based Service Cooperation”
Presented at: International Conference on Advanced Information Systems Engineering
Responsible partner: University of Oulu (UOULU)
FRACTAL project relevance: To solve the issues of trust and latency in data sharing between stakeholders within the Intelligent Traffic Systems, we propose a decentralized framework that enables smart contracts between traffic data producers and consumers based on blockchain. 

21. “A dark and stormy night: Reallocation storms in edge computing”
Submitted to: EURASIP Journal on Wireless Communications and Networking
Responsible partner: University of Oulu (UOULU)
FRACTAL project relevance: The article further expands on our earlier anaysis of reallocation storms in edge computing (published in the conference artice “Weathering the reallocation storm: A large-scale analysis of edge server workload” in 2021), a phenomenon which under certain circumstances causes massive unnecessary traffic in large edge networks. This is relevant for WP6 in Fractal. Efficient resource usage in edge computing requires clever allocation of the workload of application components. In this paper, we show that under certain circumstances, the number of superfluous workload reallocations from one edge server to another may grow to a significant proportion of all user tasks—a phenomenon we present as a reallocation storm. 

22. “Sentient Spaces: Intelligent Totem Use Case in the ECSEL FRACTAL Project”
Published to: TBA
Responsible partner: all Italian partners
FRACTAL project relevance: TBA

23. “The “Great Beauty” of Diversity: Smart Totems to Promote Gender Uniqueness”
Published to: 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)
Responsible partner: University of Valencia (UNIVAQ)
FRACTAL project relevance: This paper presents an Internet-of-Things solution represented by smart totems for advertisement and wayfinding services within advanced ICT-based shopping malls, that are conceived as a sentient space. To take into account the specificity of final users and to increase awareness of the gender uniqueness in the design of Internet-of-Things, a User-Centered Design methodology has been used. 

24. “Understanding and Mitigating Memory Interference in FPGA-based HeSoCs”
Published to: TBA
Responsible partner: UNIMORE
FRACTAL project relevance: TBA

25. “Unboxing the Sand: on Deploying Safety Measures in the Programmable Logic of COTS MPSoCs”
Published to: TBA
Responsible partner: Barcelona Supercomputing Center (BSC)
FRACTAL project relevance: TBA

26. “SafeSoftDR: A Library to Enable Software-based Diverse Redundancy for Safety-Critical Tasks”
Published to: TBA
Responsible partner: Barcelona Supercomputing Center (BSC)
FRACTAL project relevance: TBA