Yi-Chung Chen

Bio: Yi-Chung Chen is an academic researcher from New York University. The author has contributed to research in topics: Field-programmable gate array & Resistive random-access memory. The author has an hindex of 8, co-authored 14 publications receiving 190 citations. Previous affiliations of Yi-Chung Chen include University of Pittsburgh & University of Manchester.

Non-volatile 3D stacking RRAM-based FPGA

Abstract: We demonstrates a novel Field-Programmable Gate Array (FPGA) structure based on Resistive Random Access Memory (RRAM) system. RRAM is a non-volatile memory device which is compatible to CMOS Back End of Line (BEOL) process with only 4F2 area per cell. We use a 1R system memory for logic element, Look-Up-Table (LUT), with three dimension stacking structure. The proposed 2R memory system is for routing elements, Switch Block (SB) and Connection Block (CB), with Complementary Resistive Switches (CRS) structure. Both three dimension stacking and CRS structure are crossbar-like structure to further improve density of the FPGA. The proposed design is different from modern FPGA with Static Random Access Memory (SRAM) system, RRAM-based FPGA has benefits of non-volatility, smaller area, and flexibility of configuration. A bit-addressable LUT is introduced with function of run-time programming memory cells of LUT, which is also known as Distributed Random Access Memory (D-RAM). Based on our simulation results, 62.7% of area reduction and 34% of delay improvement can be achieved compared to the conventional FPGA.

The 3-D Stacking Bipolar RRAM for High Density

Abstract: For its simple structure, high density, and good scalability, the resistive random access memory (RRAM) has emerged as one of the promising candidates for large data storage in computing systems. Moreover, building up RRAM in a 3-D stacking structure further boosts its advantage in array density. Conventionally, multiple bipolar RRAM layers are piled up vertically separated with isolation material to prevent signal interference between the adjacent memory layers. The process of the isolation material increases the fabrication cost and brings in the potential reliability issue. To alleviate the situation, we introduce two novel 3-D stacking structures built upon bipolar RRAM crossbars that eliminate the isolation layers. The bigroup operation scheme dedicated for the proposed designs to enable multilayer accesses while avoiding the overwriting induced by the cross-layer disturbance is also presented. Our simulation results show that the proposed designs can increase the capacity of a memory island to 8K-bits (i.e., eight layers of 32 × 32 crossbar arrays) while maintaining the sense margin in the worst case configuration greater than 20% of the maximal sensing voltage.

The 3D Stacking Bipolar RRAM for High Density

Abstract: For its simple structure, high density, and good scalability, the resistive random access memory (RRAM) has emerged as one of the promising candidates for large data storage in computing systems. Moreover, building up RRAM in a 3-D stacking structure further boosts its advantage in array density. Conventionally, multiple bipolar RRAM layers are piled up vertically separated with isolation material to prevent signal interference between the adjacent memory layers. The process of the isolation material increases the fabrication cost and brings in the potential reliability issue. To alleviate the situation, we introduce two novel 3-D stacking structures built upon bipolar RRAM crossbars that eliminate the isolation layers. The bigroup operation scheme dedicated for the proposed designs to enable multilayer accesses while avoiding the overwriting induced by the cross-layer disturbance is also presented. Our simulation results show that the proposed designs can increase the capacity of a memory island to 8K-bits (i.e., eight layers of 32 × 32 crossbar arrays) while maintaining the sense margin in the worst case configuration greater than 20% of the maximal sensing voltage.

A Look Up Table design with 3D bipolar RRAMs

Abstract: Look Up Table (LUT) is a basic configurable logic element in Field Programmable Gate Arrays (FPGAs). In a commercial product, Static Random Access Memory (SRAM) has been widely used in each LUT to store configured logic. Recently, emerging Resistive RAM (RRAM) has attracted a lot of attention for its high density and non-volatility. In this work, we explore a novel LUT design with bipolar RRAM devices. To obtain design efficiency, a 3D high-density interleaved memory structure is introduced in the proposed LUT. The corresponding peripheral circuits were developed with TSMC 0.18µm technology node. Compared to the traditional SRAM-based FPGA, the RRAM-based LUT demonstrates advantages such as a eliminating initialization stage, a much higher density with 56% area reduction, a bit-addressable write scheme, dynamic reconfiguration, and better flexibility in supporting various configurations.

3D-HIM: A 3D High-density Interleaved Memory for bipolar RRAM design

Abstract: Because of its simple structure, high density and good scalability, resistive random access memory (RRAM) is expected to be a promising candidate to substitute traditional data storage devices, e.g., hard-disk drive (HDD). In a conventional three-dimensional (3D) bipolar RRAM design, an isolation layer is inserted between two adjacent memory layers. The fabrication of the isolation layer introduces the extra process complexity, increases fabrication cost, and causes some potential reliability issues. In this paper, we propose a 3D High-density Interleaved Memory (3D-HIM) design for bipolar RRAM, which can eliminate the need for forming isolation layers and further improve the density of the memory island. Meanwhile, we propose a Bi-Group Operation Scheme for 3D-HIM to access multiple cells among multiple layers and to avoid unexpected overwriting. The simulation results show that the proposed design is promising for a 3D stacking RRAM application with acceptable operation margin for a 32 × 32 × 8 array in a memory island. The sensing margin degradation and programming bias confine the size of the array due to sneak path conducting currents. We diminish impact of sneak path conducting current by applying a high Ron RRAM device which can be achieved by a small-scale RRAM device.

Conduction Mechanism of Valence Change Resistive Switching Memory: A Survey

Abstract: Resistive switching effect in transition metal oxide (TMO) based material is often associated with the valence change mechanism (VCM). Typical modeling of valence change resistive switching memory consists of three closely related phenomena, i.e., conductive filament (CF) geometry evolution, conduction mechanism and temperature dynamic evolution. It is widely agreed that the electrochemical reduction-oxidation (redox) process and oxygen vacancies migration plays an essential role in the CF forming and rupture process. However, the conduction mechanism of resistive switching memory varies considerably depending on the material used in the dielectric layer and selection of electrodes. Among the popular observations are the Poole-Frenkel emission, Schottky emission, space-charge-limited conduction (SCLC), trap-assisted tunneling (TAT) and hopping conduction. In this article, we will conduct a survey on several published valence change resistive switching memories with a particular interest in the I-V characteristic and the corresponding conduction mechanism.

Parallel CAD: Algorithm Design and Programming Special Section Call for Papers TODAES: ACM Transactions on Design Automation of Electronic Systems

Abstract: High-performance parallel computer architecture and systems have been improved at a phenomenal rate. In the meantime, VLSI computer-aided design (CAD) software for multibillion-transistor IC design has become increasingly complex and requires prohibitively high computational resources. Recent studies have shown that, numerous CAD problems, with their high computational complexity, can greatly benefit from the fast-increasing parallel computation capabilities. However, parallel programming imposes big challenges for CAD applications. Fully exploiting the computational power of emerging general-purpose and domain-specific multicore/many-core processor systems, calls for fundamental research and engineering practice across every stage of parallel CAD design, from algorithm exploration, programming models, design-time and run-time environment, to CAD applications, such as verification, optimization, and simulation. This journal special section will cover recent progress on parallel CAD research, including algorithm foundations, programming models, parallel architectural-specific optimization, and verification. More specifically, papers with in-depth and extensive coverage of the following topics will be considered, as well as other topics relevant to the design of parallel CAD algorithms and software tools. 1. Parallel algorithm design and specification for CAD applications 2. Parallel programming models and languages of particular use in CAD 3. Runtime support and performance optimization for CAD applications 4. Parallel architecture-specific design and optimization for CAD applications 5. Parallel program debugging and verification techniques particularly relevant for CAD The papers should be submitted via the Manuscript Central website and should adhere to standard ACM TODAES formatting requirements (http://todaes.acm.org/). The page count limit is 25.

RRAM Crossbar Array With Cell Selection Device: A Device and Circuit Interaction Study

Abstract: The resistive random access memory (RRAM) crossbar array has been extensively studied as one of the most promising candidates for future high-density nonvolatile memory technology. However, some problems caused by circuit and device interaction, such as sneak leakage paths, result in limited array size and large power consumption, which degrade the array performance significantly. Thus, the analysis on circuit and device interaction issue is imperative. In this paper, a simulation method is developed to investigate the critical issues correlated with the interaction between devices and the circuit. The simulations show that a large off/on ratio of resistance states of RRAM is beneficial for large readout margin (i.e., array size). The existence of the selector connected in series with an RRAM device can eliminate the need for high Ron resistance, which is critical for the array consisted of only RRAM cells. The readout margin is more sensitive to the variation of Ron and is determined by the nonlinearity of the I-V characteristics of RRAM, whereas the nonlinear characteristics of the selector device are beneficial for a larger readout margin. An optimal design scheme for turn-on voltage and conductance of the selector is proposed based on the simulation.

Design and Optimization of Nonvolatile Multibit 1T1R Resistive RAM

Abstract: Memristor-based random access memory (RAM) is being explored as a potential replacement for flash memory to sustain the historic trends in the improvement of density, access time, and energy consumption of nonvolatile memory. In this paper, we present the detailed functionality of multibit one-transistor one-memristor (1T1R) cell-based memory arrays, and propose circuit-level performance and energy models for an individual memory cell and the memory array as a whole. We consider titanium dioxide (TiO 2 )and hafnium oxide (HfO x )based memristors, and for these technologies, there is a sub-10% difference between energy and performance computed using our models and HSPICE simulations. Using a performance-driven design approach, the energy-optimized TiO 2 -based resistive RAM (RRAM) array consumes the least write (4.06 pJ/b) and read energy (188 fJ/b) when storing 3 b/cell for 100-ns write and 1-ns read access times. Similarly, HfO x -based RRAM array consumes the least write (365 fJ/b) and read energy (173 fJ/b) when storing 3 b/cell for 1-ns write and 200-ns read access times. We also present a detailed analysis of the implications of process, voltage, and temperature variations on the performance and energy consumption of a multibit RRAM cell.