Experimental photonic quantum memristor


Abstract "Memristive devices are a class of physical systems with history-dependent dynamics characterized by signature hysteresis loops in their input–output relations. In the past few decades, memristive devices have attracted enormous interest in electronics. This is because memristive dynamics is very pervasive in nanoscale devices, and has potentially groundbreaking applications ranging... » read more

An Energy-Efficient DRAM Cache Architecture for Mobile Platforms With PCM-Based Main Memory


Abstract "A long battery life is a first-class design objective for mobile devices, and main memory accounts for a major portion of total energy consumption. Moreover, the energy consumption from memory is expected to increase further with ever-growing demands for bandwidth and capacity. A hybrid memory system with both DRAM and PCM can be an attractive solution to provide additional capacity ... » read more

NAND and NOR logic-in-memory comprising silicon nanowire feedback field-effect transistors


Abstract: "The processing of large amounts of data requires a high energy efficiency and fast processing time for high-performance computing systems. However, conventional von Neumann computing systems have performance limitations because of bottlenecks in data movement between separated processing and memory hierarchy, which causes latency and high power consumption. To overcome this hindra... » read more

Quantifying Rowhammer Vulnerability for DRAM Security


Abstract: "Rowhammer is a memory-based attack that leverages capacitive-coupling to induce faults in modern dynamic random-access memory (DRAM). Over the last decade, a significant number of Rowhammer attacks have been presented to reveal that it is a severe security issue capable of causing privilege escalations, launching distributed denial-of-service (DDoS) attacks, and even runtime attack ... » read more

Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-in-Memory Hardware


Abstract "Many modern workloads such as neural network inference and graph processing are fundamentally memory-bound. For such workloads, data movement between memory and CPU cores imposes a significant overhead in terms of both latency and energy. A major reason is that this communication happens through a narrow bus with high latency and limited bandwidth, and the low data reuse in memory-bo... » read more

SparseP: Towards Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Systems


Abstract "Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks and can yield significant performance and energy improvements in parallel applications by alleviating data access costs. Real PIM systems can provide high levels of parallelism, large aggregate memory bandwi... » read more

Non-destructive Thickness Characterisation of 3D Multilayer Semiconductor Devices Using Optical Spectral Measurements and Machine Learning


Abstract: "Three-dimensional (3D) semiconductor devices can address the limitations of traditional two-dimensional (2D) devices by expanding the integration space in the vertical direction. A 3D NOT-AND (NAND) flash memory device ispresently the most commercially successful 3D semiconductor device. It vertically stacks more than 100 semiconductor material layers to provide more storage capac... » read more

Comprehensive Model of Electron Conduction in Oxide-Based Memristive Devices


Abstract "Memristive devices are two-terminal devices that can change their resistance state upon application of appropriate voltage stimuli. The resistance can be tuned over a wide resistance range enabling applications such as multibit data storage or analog computing-in-memory concepts. One of the most promising classes of memristive devices is based on the valence change mechanism in oxide... » read more

Hybrid architecture based on two-dimensional memristor crossbar array and CMOS integrated circuit for edge computing


Abstract "The fabrication of integrated circuits (ICs) employing two-dimensional (2D) materials is a major goal of semiconductor industry for the next decade, as it may allow the extension of the Moore’s law, aids in in-memory computing and enables the fabrication of advanced devices beyond conventional complementary metal-oxide-semiconductor (CMOS) technology. However, most circuital demons... » read more

A crossbar array of magnetoresistive memory devices for in-memory computing


Samsung has demonstrated the world’s first in-memory computing technology based on MRAM. Samsung has a paper on the subject in Nature. This paper showcases Samsung’s effort to merge memory and system semiconductors for next-generation artificial intelligence (AI) chips. Abstract "Implementations of artificial neural networks that borrow analogue techniques could potentially offer low-po... » read more

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