NISTT: A Non-Intrusive SystemC-TLM 2.0 Tracing Tool

The increasing complexity of systems-on-a-chip requires the continuous development of electronic design automation tools. Nowadays, the simulation of systems-on-a-chip using virtual platforms is common. Virtual platforms enable hardware/software co-design to shorten the time to market, offer insights into the models, and allow debugging of the simulated hardware. Profiling tools are required to improve the usability of virtual platforms. During simulation, these tools capture data that are evaluated afterward. Those data can reveal information about the simulation itself and the software executed on the platform. This work presents the tracing tool NISTT that can profile SystemC-TLM-2.0-based virtual platforms. NISTT is implemented in a completely non-intrusive way. That means no changes in the simulation are needed, the source code of the simulation is not required, and the traced simulation does not need to contain debug symbols. The standardized SystemC application programming interface guarantees the compatibility of NISTT with other simulations. The strengths of NISTT are demonstrated in a case study. Here, NISTT is connected to a virtual platform and traces the boot process of Linux. After the simulation, the database created by NISTT is evaluated, and the results are visualized. Furthermore, the overhead of NISTT is quantified. It is shown that NISTT has only a minor influence on the overall simulation performance.Comment: PREPRINT - accepted by 30th IFIP/IEEE International Conference on Very Large Scale Integration 2022 (VLSI-SoC 2022

Mapping of CNNs on multi-core RRAM-based CIM architectures

RRAM-based multi-core systems improve the energy efficiency and performance of CNNs. Thereby, the distributed parallel execution of convolutional layers causes critical data dependencies that limit the potential speedup. This paper presents synchronization techniques for parallel inference of convolutional layers on RRAM-based CIM architectures. We propose an architecture optimization that enables efficient data exchange and discuss the impact of different architecture setups on the performance. The corresponding compiler algorithms are optimized for high speedup and low memory consumption during CNN inference. We achieve more than 99% of the theoretical acceleration limit with a marginal data transmission overhead of less than 4% for state-of-the-art CNN benchmarks

Fault Injection in Native Logic-in-Memory Computation on Neuromorphic Hardware

Logic-in-memory (LIM) describes the execution of logic gates within memristive crossbar structures, promising to improve performance and energy efficiency. Utilizing only binary values, LIM particularly excels in accelerating binary neural networks, shifting it in the focus of edge applications. Considering its potential, the impact of faults on BNNs accelerated with LIM still lacks investigation. In this paper, we propose faulty logic-in-memory (FLIM), a fault injection platform capable of executing full-fledged BNNs on LIM while injecting in-field faults. The results show that FLIM runs a single MNIST picture 66754x faster than the state of the art by offering a fine-grained fault injection methodology

Novel Cell-Free Strategy for Therapeutic Angiogenesis: In Vitro Generated Conditioned Medium Can Replace Progenitor Cell Transplantation

BACKGROUND: Current evidence suggests that endothelial progenitor cells (EPC) contribute to ischemic tissue repair by both secretion of paracrine factors and incorporation into developing vessels. We tested the hypothesis that cell-free administration of paracrine factors secreted by cultured EPC may achieve an angiogenic effect equivalent to cell therapy. METHODOLOGY/PRINCIPAL FINDINGS: EPC-derived conditioned medium (EPC-CM) was obtained from culture expanded EPC subjected to 72 hours of hypoxia. In vitro, EPC-CM significantly inhibited apoptosis of mature endothelial cells and promoted angiogenesis in a rat aortic ring assay. The therapeutic potential of EPC-CM as compared to EPC transplantation was evaluated in a rat model of chronic hindlimb ischemia. Serial intramuscular injections of EPC-CM and EPC both significantly increased hindlimb blood flow assessed by laser Doppler (81.2+/-2.9% and 83.7+/-3.0% vs. 53.5+/-2.4% of normal, P<0.01) and improved muscle performance. A significantly increased capillary density (1.62+/-0.03 and 1.68+/-0.05/muscle fiber, P<0.05), enhanced vascular maturation (8.6+/-0.3 and 8.1+/-0.4/HPF, P<0.05) and muscle viability corroborated the findings of improved hindlimb perfusion and muscle function. Furthermore, EPC-CM transplantation stimulated the mobilization of bone marrow (BM)-derived EPC compared to control (678.7+/-44.1 vs. 340.0+/-29.1 CD34(+)/CD45(-) cells/1x10(5) mononuclear cells, P<0.05) and their recruitment to the ischemic muscles (5.9+/-0.7 vs. 2.6+/-0.4 CD34(+) cells/HPF, P<0.001) 3 days after the last injection. CONCLUSIONS/SIGNIFICANCE: Intramuscular injection of EPC-CM is as effective as cell transplantation for promoting tissue revascularization and functional recovery. Owing to the technical and practical limitations of cell therapy, cell free conditioned media may represent a potent alternative for therapeutic angiogenesis in ischemic cardiovascular diseases

NeuroHammer: Inducing Bit-Flips in Memristive Crossbar Memories

Emerging non-volatile memory (NVM) technologies offer unique advantages in energy efficiency, latency, and features such as computing-in-memory. Consequently, emerging NVM technologies are considered an ideal substrate for computation and storage in future-generation neuromorphic platforms. These technologies need to be evaluated for fundamental reliability and security issues. In this paper, we present \emph{NeuroHammer}, a security threat in ReRAM crossbars caused by thermal crosstalk between memory cells. We demonstrate that bit-flips can be deliberately induced in ReRAM devices in a crossbar by systematically writing adjacent memory cells. A simulation flow is developed to evaluate NeuroHammer and the impact of physical parameters on the effectiveness of the attack. Finally, we discuss the security implications in the context of possible attack scenarios