Spin–orbit torque engineering in β-W/CoFeB heterostructures with W–Ta or W–V alloy layers between β-W and CoFeB


Abstract "The spin–orbit torque (SOT) resulting from a spin current generated in a nonmagnetic transition metal layer offers a promising magnetization switching mechanism for spintronic devices. To fully exploit this mechanism, in practice, materials with high SOT efficiencies are indispensable. Moreover, new materials need to be compatible with semiconductor processing. This study introduce... » read more

Field-free spin-orbit torque-induced switching of perpendicular magnetization in a ferrimagnetic layer with a vertical composition gradient


Abstract "Current-induced spin-orbit torques (SOTs) are of interest for fast and energy-efficient manipulation of magnetic order in spintronic devices. To be deterministic, however, switching of perpendicularly magnetized materials by SOT requires a mechanism for in-plane symmetry breaking. Existing methods to do so involve the application of an in-plane bias magnetic field, or incorporation o... » read more

A review of interconnect materials used in emerging memory device packaging: first- and second-level interconnect materials


Abstract "The main motivation of this review is to study the evolution of first and second level of interconnect materials used in memory device semiconductor packaging. Evolutions of bonding wires from gold (Au) to silver (Ag) or copper (Cu) have been reported and studied in previous literatures for low-cost solution, but Au wire still gives highest rating in terms of the performance of tempe... » read more

NeuroSim Simulator for Compute-in-Memory Hardware Accelerator: Validation and Benchmark


Abstract:   "Compute-in-memory (CIM) is an attractive solution to process the extensive workloads of multiply-and-accumulate (MAC) operations in deep neural network (DNN) hardware accelerators. A simulator with options of various mainstream and emerging memory technologies, architectures, and networks can be a great convenience for fast early-stage design space exploration of CIM hardw... » read more

Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices


Abstract:  "Recent advances in deep learning have been driven by ever-increasing model sizes, with networks growing to millions or even billions of parameters. Such enormous models call for fast and energy-efficient hardware accelerators. We study the potential of Analog AI accelerators based on Non-Volatile Memory, in particular Phase Change Memory (PCM), for software-equivalent accurate i... » read more

Benchmarking Highly Parallel Hardware for Spiking Neural Networks in Robotics


Abstract: "Animal brains still outperform even the most performant machines with significantly lower speed. Nonetheless, impressive progress has been made in robotics in the areas of vision, motion- and path planning in the last decades. Brain-inspired Spiking Neural Networks (SNN) and the parallel hardware necessary to exploit their full potential have promising features for robotic applica... » read more

Factoring 2048-bit RSA Integers in 177 Days with 13 436 Qubits and a Multimode Memory


Abstract: "We analyze the performance of a quantum computer architecture combining a small processor and a storage unit. By focusing on integer factorization, we show a reduction by several orders of magnitude of the number of processing qubits compared with a standard architecture using a planar grid of qubits with nearest-neighbor connectivity. This is achieved by taking advantage of a tem... » read more

All-inorganic perovskite quantum dot light-emitting memories


Abstract "Field-induced ionic motions in all-inorganic CsPbBr3 perovskite quantum dots (QDs) strongly dictate not only their electro-optical characteristics but also the ultimate optoelectronic device performance. Here, we show that the functionality of a single Ag/CsPbBr3/ITO device can be actively switched on a sub-millisecond scale from a resistive random-access memory (RRAM) to a light-e... » read more

QUAC-TRNG: High-Throughput True Random Number Generation Using Quadruple Row Activation in Commodity DRAM Chips


Abstract "True random number generators (TRNG) sample random physical processes to create large amounts of random numbers for various use cases, including security-critical cryptographic primitives, scientific simulations, machine learning applications, and even recreational entertainment. Unfortunately, not every computing system is equipped with dedicated TRNG hardware, limiting the applicat... » read more

HARP: Practically and Effectively Identifying Uncorrectable Errors in Memory Chips That Use On-Die Error-Correcting Codes


Abstract: "State-of-the-art techniques for addressing scaling-related main memory errors identify and repair bits that are at risk of error from within the memory controller. Unfortunately, modern main memory chips internally use on-die error correcting codes (on-die ECC) that obfuscate the memory controller's view of errors, complicating the process of identifying at-risk bits (i.e., error pr... » read more

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