HECTOR-V: A Heterogeneous CPU Architecture for a Secure RISC-V Execution Environment


Summary "To ensure secure and trustworthy execution of applications, vendors frequently embed trusted execution environments into their systems. Here, applications are protected from adversaries, including a malicious operating system. TEEs are usually built by integrating protection mechanisms directly into the processor or by using dedicated external secure elements. However, both of these... » read more

A graph placement methodology for fast chip design


Abstract "Chip floorplanning is the engineering task of designing the physical layout of a computer chip. Despite five decades of research1, chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to produce manufacturable layouts. Here we present a deep reinforcement learning approach to chip floorplanning. In under six hours, our method autom... » read more

High-Voltage, High-Current Electrical Switching Discharge Synthesis of ZnO Nanorods: A New Method toward Rapid and Highly Tunable Synthesis of Oxide Semiconductors in Open Air and Water for Optoelectronic Applications


Abstract: "A novel method of oxide semiconductor nanoparticle synthesis is proposed based on high-voltage, high-current electrical switching discharge (HVHC-ESD). Through a subsecond discharge in the HVHC-ESD method, we successfully synthesized zinc oxide (ZnO) nanorods. Crystallography and optical and electrical analyses approve the high crystal-quality and outstanding optoelectronic charac... » read more

Accelerating Inference of Convolutional Neural Networks Using In-memory Computing


Abstract: "In-memory computing (IMC) is a non-von Neumann paradigm that has recently established itself as a promising approach for energy-efficient, high throughput hardware for deep learning applications. One prominent application of IMC is that of performing matrix-vector multiplication in (1) time complexity by mapping the synaptic weights of a neural-network layer to the devices of an ... » read more

Neuromorphic electronics based on copying and pasting the brain


Abstract: "Reverse engineering the brain by mimicking the structure and function of neuronal networks on a silicon integrated circuit was the original goal of neuromorphic engineering, but remains a distant prospect. The focus of neuromorphic engineering has thus been relaxed from rigorous brain mimicry to designs inspired by qualitative features of the brain, including event-driven sign... » read more

Sputtered transparent electrodes for optoelectronic devices: Induced damage and mitigation strategies


Abstract: Summary "Transparent electrodes and metal contacts deposited by magnetron sputtering find applications in numerous state-of-the-art optoelectronic devices, such as solar cells and light-emitting diodes. However, the deposition of such thin films may damage underlying sensitive device layers due to plasma emission and particle impact. Inserting a buffer layer to shield against such da... » read more

Substitutional synthesis of sub-nanometer InGaN/GaN quantum wells with high indium content


Abstract "InGaN/GaN quantum wells (QWs) with sub-nanometer thickness can be employed in short-period superlattices for bandgap engineering of efficient optoelectronic devices, as well as for exploiting topological insulator behavior in III-nitride semiconductors. However, it had been argued that the highest indium content in such ultra-thin QWs is kinetically limited to a maximum of 33%, narro... » read more

Data-driven Scheduling for High-mix and Low-volume Production in Semiconductor Assembly and Testing


Abstract: The objective of this research is to improve scheduling decisions in high-mix low-volume (HMLV) production environments. Unique characteristics of HMLV semiconductor assembly and testing operations include: (1) Diversified Product Lines: To respond to global competition and different customer needs, manufacturers are providing diversified products to different consumers; (2) Unrelate... » read more

Roadmap on organic–inorganic hybrid perovskite semiconductors and devices


ABSTRACT Metal halide perovskites are the first solution processed semiconductors that can compete in their functionality with conventional semiconductors, such as silicon. Over the past several years, perovskite semiconductors have reported breakthroughs in various optoelectronic devices, such as solar cells, photodetectors, light emitting and memory devices, and so on. Until now, perovskit... » read more

Energy-efficient memcapacitor devices for neuromorphic computing


Abstract Data-intensive computing operations, such as training neural networks, are essential for applications in artificial intelligence but are energy intensive. One solution is to develop specialized hardware onto which neural networks can be directly mapped, and arrays of memristive devices can, for example, be trained to enable parallel multiply–accumulate operations. Here we show that ... » read more

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