Analytical modelling of the transport in analog filamentary conductive-metal-oxide/HfO ReRAM devices.

The recent co-optimization of memristive technologies and programming algorithms enabled neural networks training with in-memory computing systems. In this context, novel analog filamentary conductive-metal-oxide (CMO)/HfO redox-based resistive switching memory (ReRAM) represents a key technology. Despite device performance enhancements reported in literature, the underlying mechanism behind resistive switching is not fully understood.

A multi-timescale synaptic weight based on ferroelectric hafnium zirconium oxide.

Brain-inspired computing emerged as a forefront technology to harness the growing amount of data generated in an increasingly connected society. The complex dynamics involving short- and long-term memory are key to the undisputed performance of biological neural networks. Here, we report on sub-µm-sized artificial synaptic weights exploiting a combination of a ferroelectric space charge effect and oxidation state modulation in the oxide channel of a ferroelectric field effect transistor.

Neuromorphic Systems Design by Matching Inductive Biases to Hardware Constraints.

Neuromorphic systems are designed with careful consideration of the physical properties of the computational substrate they use. Neuromorphic engineers often exploit physical phenomena to directly implement a desired functionality, enabled by "the isomorphism between physical processes in different media" (Douglas et al., 1995).

Back-End, CMOS-Compatible Ferroelectric Field-Effect Transistor for Synaptic Weights.

Neuromorphic computing architectures enable the dense colocation of memory and processing elements within a single circuit. This colocation removes the communication bottleneck of transferring data between separate memory and computing units as in standard von Neuman architectures for data-critical applications including machine learning. The essential building blocks of neuromorphic systems are nonvolatile synaptic elements such as memristors.

Polymer waveguides for electro-optical integration in data centers and high-performance computers.

To satisfy the intra- and inter-system bandwidth requirements of future data centers and high-performance computers, low-cost low-power high-throughput optical interconnects will become a key enabling technology. To tightly integrate optics with the computing hardware, particularly in the context of CMOS-compatible silicon photonics, optical printed circuit boards using polymer waveguides are considered as a formidable platform. IBM Research has already demonstrated the essential silicon photonics and interconnection building blocks.

Flip-chip optical couplers with scalable I/O count for silicon photonics.

A scalable and tolerant optical interfacing method based on flip-chip bonding is developed for silicon photonics packaging. Bidirectional optical couplers between multiple silicon-on-insulator waveguides and single-mode polymer waveguides are designed and fabricated. Successful operation is verified experimentally in the 1530-1570 nm spectral window.

Cascaded Mach-Zehnder wavelength filters in silicon photonics for low loss and flat pass-band WDM (de-)multiplexing.

We present 1-to-8 wavelength (de-)multiplexer devices based on a binary tree of cascaded Mach-Zehnder-like lattice filters, and manufactured using a 90 nm CMOS-integrated silicon photonics technology. We demonstrate that these devices combine a flat pass-band over more than 50% of the channel spacing with low insertion loss of less than 1.6 dB, and have a small device size of approximately 500 × 400 µm.