Computer architecture

Impact of Aging, Self-Heating, and Parasitics Effects on NSFET and CFET

Impact of Aging, Self-Heating, and Parasitics Effects on NSFET and CFET 150 150

Abstract:

This work presents a comparative analysis of complementary field-effect transistor (CFET) and nanosheet FET (NSFET) architectures, with a focus on self-heating effects (SHEs), negative bias temperature instability (NBTI), hot carrier degradation (HCD), and the impact of back-end-of-line (BEOL) parasitics on standard cell performance. NBTI degradation is modeled using a framework …

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A Microscaling Multi-Mode Gain-Cell Computing-in-Memory Macro for Advanced AI Edge Device

A Microscaling Multi-Mode Gain-Cell Computing-in-Memory Macro for Advanced AI Edge Device 150 150

Abstract:

The microscaling (MX) format is an emerging data representation that quantizes high-bitwidth floating-point (FP) values into low-bitwidth FP-like values with a shared-scale (SS) exponent. When implemented with computing-in-memory (CIM), MX allows an attractive tradeoff between accuracy and hardware efficiency for specific neural network (NN) workloads. This work presents the first …

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A 168 nW to 44.3 Mb/s Adaptable TRNG With 400 mV Attack-Resilient Hybrid RO Core

A 168 nW to 44.3 Mb/s Adaptable TRNG With 400 mV Attack-Resilient Hybrid RO Core 150 150

Abstract:

This letter presents an adaptable ring oscillator (RO)-true random number generator (TRNG) that removes the fixed power–throughput tradeoff by selecting delay-cell physics at run time. A hybrid core uses a current-starved inverter in low-power (LP) mode to amplify slew-limited jitter for high bit-efficiency at low frequency, and a …

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Understanding Reliability Trade-Offs in 1T-nC and 2T-nC FeRAM Designs

Understanding Reliability Trade-Offs in 1T-nC and 2T-nC FeRAM Designs 150 150

Abstract:

Ferroelectric random access memory (FeRAM) is a promising candidate for energy-efficient nonvolatile memory, particularly for logic-in-memory and compute-in-memory (CIM) applications. Among the available cell architectures, One-Transistor–n-Capacitor (1T-nC) and two-transistor–n-capacitor (2T-nC) FeRAMs each offer distinct trade-offs in density, scalability, and reliability. In this work, we present a comparative study …

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A 28-Gb/mm2 4XX-Layer 1-Tb 3-b/Cell WF-Bonding 3D-nand Flash With 5.6-Gb/s/Pin IOs

A 28-Gb/mm2 4XX-Layer 1-Tb 3-b/Cell WF-Bonding 3D-nand Flash With 5.6-Gb/s/Pin IOs 150 150

Abstract:

The challenge of evolving to create a memory that is shrinking compared to the previous generation while satisfying the high performance and low power required for flash memory has been present in every generation, but the recent rapid change to artificial intelligence (AI) trends is very tough, as the level …

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Beyond Backside Power: Backside Signal Routing as Technology Booster for Standard-Cell Scaling

Beyond Backside Power: Backside Signal Routing as Technology Booster for Standard-Cell Scaling 150 150

Abstract:

Advances in process technology enabling backside metals (BSMs) and contacts offer new design–technology co-optimization (DTCO) opportunities to further enhance power, performance, and area gains (PPA) in sub-3-nm nodes. This work exploits backside (BS) contact technology within standard cells to extend both signal and clock routing to BSM layers, …

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CORDIC-Less Digital Polar Transmitter Architecture Based on Delta-Sigma Modulator

CORDIC-Less Digital Polar Transmitter Architecture Based on Delta-Sigma Modulator 150 150

Abstract:

Conventional digital polar transmitters (TXs) suffer from limited power efficiency and linearity due to the multi-bit nature of intermediate signals. This work proposes a digital polar TX architecture that avoids such drawbacks by reducing the bit count of TX signals. The proposed TX oversamples and quantizes multi-bit I/Q inputs …

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Opal: A 16-nm Coarse-Grained Reconfigurable Array SoC for Full Sparse Machine Learning Applications

Opal: A 16-nm Coarse-Grained Reconfigurable Array SoC for Full Sparse Machine Learning Applications 150 150

Abstract:

Sparsity has recently attracted increased attention in the machine learning (ML) community due to its potential to improve performance and energy efficiency by eliminating ineffectual computations. As ML models evolve rapidly, reconfigurable architectures, such as coarse-grained reconfigurable arrays (CGRAs), are being explored to adapt to and accelerate emerging models. Previous …

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A 19.5-GHz Radiation-Hardened Sub-Sampled PLL With Quad-Core VCO in 16-nm FinFET Achieving Sub-50 fs Jitter

A 19.5-GHz Radiation-Hardened Sub-Sampled PLL With Quad-Core VCO in 16-nm FinFET Achieving Sub-50 fs Jitter 150 150

Abstract:

This letter presents a radiation-hardened (rad-hard) subsampled phase-locked loop (SS-PLL) that achieves state-of-the-art jitter performance while incorporating radiation-hardened techniques to mitigate single-event-upsets (SEUs) present in the space environment. Furthermore, rad-hard techniques are incorporated in each core PLL subblock which include a rad-hard charge-pump Gm cell, a pulser circuit with triple …

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