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Human-centered Internet-of-Things (IoT) applications utilize computational algorithms such as machine learning and signal processing techniques to infer knowledge about important events such as physical activities and medical complications. The inference is typically based on data collected with wearable sensors or those embedded in the environment. A major obstacle in large-scale utilization of these...
As the number of cores increases, cache-based memory hierarchy is becoming a major problem in terms of the scalability and energy consumption. Software-managed scratchpad memories (SPM) is a scalable alternative to caches, but the benefit comes at the cost of explicit management of data. For instance, an instruction SPM needs a code management techniques to load code blocks to the SPM. This paper...
Welcome to the 35th edition of the International Conference on Computer-Aided Design! For the second year in a row, ICCAD is held in Austin, Texas. Jointly sponsored by IEEE and ACM, ICCAD is the premier forum to explore emerging technology challenges, present cutting-edge R&D solutions, record theoretical and empirical advances, and identify future roadmaps for design automation and other system-on-chip...
Single-ISA heterogeneous mobile processors integrate low-power and power-hungry CPU cores together to combine energy efficiency with high performance. While running computationally demanding applications, current power management and scheduling techniques greedily maximize quality-of-service (QoS) within thermal constraints using power-hungry cores. We show that such an approach delivers short bursts...
Power and thermal issues are the main constraints for high-performance multi-core systems. As the current technology of choice, FinFET is observed to have lower delay under higher temperature in super-threshold voltage region, an effect called temperature effect inversion (TEI). While it has been shown that system performance can be improved under power constraints, as technology aggressively scales...
We introduce a machine learning approach for distinguishing between integrated circuits fabricated in a ratified facility and circuits originating from an unknown or undesired source based on parametric measurements. Unlike earlier approaches, which seek to achieve the same objective in a general, design-independent manner, the proposed method leverages the interaction between the idiosyncrasies of...
Dummy fill insertion is widely applied to significantly improve the planarity of topographic patterns for chemical mechanical polishing process in VLSI manufacture. However, these dummies will lead to additional parasitic capacitance and deteriorate the circuit performance. The main challenge of dummy filling algorithms is how to balance multiple objectives, such as fill amount, density variation,...
Split manufacturing is a technique that allows manufacturing the transistor-level and lower metal layers of an IC at a high-end, untrusted foundry, while manufacturing only the higher metal layers at a smaller, trusted foundry. Using split manufacturing is only viable if the untrusted foundry cannot reverse engineer the higher metal layer connections (and thus the overall IC design) from the lower...
Large battery packs composed of Lithium-Ion cells are continuously gaining in importance due to their applications in Electric Vehicles (EVs) and smart energy grids. To ensure maximum lifetime, safety and performance of the battery pack, complex embedded system architectures consisting of sensors, power electronics and microcontrollers are integrated into the pack as Battery Management System (BMS)...
Formal techniques seem to be a way to cope with the exploding complexity of functional safety analysis. Here, the overall fault propagation probability to a certain safety-point in the design must be analyzed. As a consequence, the careful verification of the design is no longer sufficient. In addition, the propagation of all possible faults potentially showing up at all of the design's internal nodes...
Artificial neural networks (NN) have shown a significant promise in difficult tasks like image classification or speech recognition. Even well-optimized hardware implementations of digital NNs show significant power consumption. It is mainly due to non-uniform pipeline structures and inherent redundancy of numerous arithmetic operations that have to be performed to produce each single output vector...
Additive Manufacturing (AM) uses Cyber-Physical Systems (CPS) (e.g., 3D Printers) that are vulnerable to kinetic cyber-attacks. Kinetic cyber-attacks cause physical damage to the system from the cyber domain. In AM, kinetic cyber-attacks are realized by introducing flaws in the design of the 3D objects. These flaws may eventually compromise the structural integrity of the printed objects. In CPS,...
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