Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI- MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (~1011 neuron based) large neural networks.

/pdf/leaky-integrate-and-fire-neuron-by-charge-discharge-dynamics-1zlow0lmpg.pdf

Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET.

The impact of process variation on SRAM yield has become a serious concern in scaled technologies. In this paper, we propose a methodology to analyze the stability of an SRAM cell in the presence of random fluctuations in the device parameters. We provide a theoretical framework for characterizing the DC noise margin of a memory cell and develop models for estimating the cell failure probabilities during read and write operations. The proposed models are verified against extensive Monte-Carlo simulations and are shown to match well over the entire range of the distributions well beyond the 3-sigma extremes.

Statistical analysis of SRAM cell stability

Current status and challenges of aggressive equivalent-oxide-thickness (EOT) scaling of high-κ gate dielectrics via higher-κ ( > 20) materials and interfacial layer (IL) scavenging techniques are reviewed. La-based higher-κ materials show aggressive EOT scaling (0.5-0.8 nm), but with effective workfunction (EWF) values suitable only for n-type field-effect-transistor (FET). Further exploration for p-type FET-compatible higher-κ materials is needed. Meanwhile, IL scavenging is a promising approach to extend Hf-based high-κ dielectrics to future nodes. Remote IL scavenging techniques enable EOT scaling below 0.5 nm. Mobility-EOT trends in the literature suggest that short-channel performance improvement is attainable with aggressive EOT scaling via IL scavenging or La-silicate formation. However, extreme IL scaling (e.g., zero-IL) is accompanied by loss of EWF control and with severe penalty in reliability. Therefore, highly precise IL thickness control in an ultra-thin IL regime ( < 0.5 nm) will be the key technology to satisfy both performance and reliability requirements for future CMOS devices.

Ultimate Scaling of High-κ Gate Dielectrics: Higher-κ or Interfacial Layer Scavenging?

The impact of process variation on SRAM yield has become a serious concern in scaled technologies. In this paper, we propose a methodology to analyze the stability of an SRAM cell in the presence of random fluctuations in the device parameters. First, we develop a theoretical framework for characterizing the dc noise margin of a memory cell. The framework is based on the concept that an SRAM cell is on the verge of instability when the gain across the loop formed by the cross-coupled inverters in the cell is unity. The noise margin criteria developed in this manner can be used to verify a cell stability in the presence of arbitrary DC noise offsets at the two storage nodes in the cell. We also develop metrics for estimating the cell stability during read and write operations and verify these models by extensive Monte Carlo simulations in a 65-nm CMOS process. Our results show that the proposed robustness metrics can be used to estimate cell failure probabilities in an efficient and accurate manner.

The Impact of Random Device Variation on SRAM Cell Stability in Sub-90-nm CMOS Technologies

The POWER6trade microprocessor combines ultra-high frequency operation, aggressive power reduction, a highly scalable memory subsystem, and mainframe-like reliability, availability, and serviceability. The 341mm2 700M transistor dual-core microprocessor is fabricated in a 65nm SOI process with 10 levels of low-k copper interconnect. It operates at clock frequencies over 5GHz in high-performance applications, and consumes under 100W in power-sensitive applications.

Design of the Power6 Microprocessor

A high performance 65 nm SOI CMOS technology is presented featuring 35 nm gate length, 1.05 nm gate oxide, performance enhancement from dual stress nitride liners (DSL), and 10 wiring levels with low-k dielectric offered in the first 8 levels. DSL enhancement is shown to scale well to 65 nm with larger enhancement seen than at 90 nm design rules. A high performance 0.65/spl mu/m/sup 2/ SRAM cell is also presented. SOI allows the SRAM cell to use Metal 1 instead of Metal 2 for bit-line wiring, which lowers the capacitance and improves access times. A functional dual-core microprocessor test chip containing 76Mb SRAM cache and key execution units has been fabricated.

High performance 65 nm SOI technology with dual stress liner and low capacitance SRAM cell

This work presents a 32 nm SOI CMOS technology featuring high-k/metal gate and an SRAM cell size of 0.149 µm2. V min operation down to 0.6 V in a 16Mb SRAM array test vehicle has been demonstrated. Aggressive ground rules are achieved with 193 nm immersion lithography. High performance is enabled by hig-hk/metal gate plus innovation on strained silicon elements including embedded SiGe and dual stress liner (DSL). Gate lengths down to 25 nm have been demonstrated enabling performance without the power penalty from gate capacitance. AC drive currents of 1.55 mA/um and 1.22 mA/um have been achieved at an off-state of 100 nA/µm and V DD of 1 V for NFET and PFET, respectively. For the first time, we have also demonstrated that SOI maintains performance benefit over bulk silicon in high-k/metal gate and 32 nm ground rules.

High performance 32nm SOI CMOS with high-k/metal gate and 0.149µm 2 SRAM and ultra low-k back end with eleven levels of copper

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High performance 65 nm SOI technology with dual stress liner and low capacitance SRAM cell

High performance 32nm SOI CMOS with high-k/metal gate and 0.149µm 2 SRAM and ultra low-k back end with eleven levels of copper