Integrated circuits

OISMA: On-the-Fly In-Memory Stochastic Multiplication Architecture for Approximate Matrix Multiplication

OISMA: On-the-Fly In-Memory Stochastic Multiplication Architecture for Approximate Matrix Multiplication 150 150

Abstract:

Artificial intelligence (AI) models are currently driven by a significant upscaling of their complexity, with massive matrix-multiplication workloads representing the major computational bottleneck. In-memory computing (IMC) architectures are proposed to avoid the von Neumann bottleneck. However, both digital/binary-based and analog IMC architectures suffer from various limitations, which significantly degrade …

View on IEEE Xplore

A Complementary Positive Feedback-Assisted Current Mirror-Based Level Shifter for Energy-Efficient Level Conversion for Wide Voltage Ranges

A Complementary Positive Feedback-Assisted Current Mirror-Based Level Shifter for Energy-Efficient Level Conversion for Wide Voltage Ranges 150 150

Abstract:

A complementary positive feedback-assisted current mirror-based level shifter (CPFLS) is proposed to reliably convert subthreshold signals to higher voltages. By adopting a positive feedback structure, the CPFLS mitigates the delay degradation and short-circuit current issues inherent in a prior art, WCMLS, due to its negative feedback design. Additionally, the CPFLS …

View on IEEE Xplore

A 760 mVPP-Input-Range, 103.6dB-SNDR Direct-Digitization Sensor Readout With Pseudo-Differential Integrator and Impedance-Equalized RDAC

A 760 mVPP-Input-Range, 103.6dB-SNDR Direct-Digitization Sensor Readout With Pseudo-Differential Integrator and Impedance-Equalized RDAC 150 150

Abstract:

A high-precision, direct-digitization sensor readout (DD-RO) based on a continuous-time delta-sigma modulator (CT- $\Delta \Sigma $ M) is presented. The proposed DD-RO incorporates several key innovations to enhance performance. First, a pseudo-differential current-balancing integrator (PD-CBI) significantly extends the linear input range, whereas its intrinsically limited common-mode input range and CMRR are …

View on IEEE Xplore

HyFPCiM: A 65-nm 417-μW Error-Sensitivity-Aware FP8 Compute-in-Memory Macro

HyFPCiM: A 65-nm 417-μW Error-Sensitivity-Aware FP8 Compute-in-Memory Macro 150 150

Abstract:

This letter presents HyFPCiM, a 65-nm FP8 compute-in-memory (CiM) macro that enables sub-mW floating-point (FP) inference using error-sensitivity-aware FP partitioning (EAP). EAP maps exponent processing to a digital CiM (DCiM) path and mantissa accumulation to an analog CiM (ACiM), avoiding the power- and area-intensive adder-tree-based accumulation used in prior FP-CiM …

View on IEEE Xplore

A 3.47 NEF 175.2-dB FoMs Direct Digitization Front-End Featuring Delta Amplification Noise-Shaping SAR ADC for Biosignal Acquisition

A 3.47 NEF 175.2-dB FoMs Direct Digitization Front-End Featuring Delta Amplification Noise-Shaping SAR ADC for Biosignal Acquisition 150 150

Abstract:

This article presents a direct-digitization interface for ExG bio-signals’ readout that simultaneously achieves a high dynamic range (DR) and a low noise-efficiency factor (NEF). The proposed delta amplification (DA) and feedback cancellation technique reduce both the input and output ranges of the first amplifier, thus allowing the use of a …

View on IEEE Xplore

Denim: Heterogeneous Compute-in-Memory Accelerator Exploiting Denoising–Similarity for Diffusion Models

Denim: Heterogeneous Compute-in-Memory Accelerator Exploiting Denoising–Similarity for Diffusion Models 150 150

Abstract:

Diffusion models have recently revolutionized the field of image synthesis due to their ability to generate photorealistic images. However, one of the main drawbacks of diffusion models is that the image generation process is expensive. Large image-to-image networks have to be applied multiple times in order to iteratively optimize the …

View on IEEE Xplore

A Time-Domain CNN Engine With Adaptive-Precision Computing and Threshold-Controllable Prediction for Edge Computing

A Time-Domain CNN Engine With Adaptive-Precision Computing and Threshold-Controllable Prediction for Edge Computing 150 150

Abstract:

With the growing demand for energy-efficient convolutional neural network (CNN) accelerators in edge intelligence, conventional digital CNN processors with fixed precision incur excessive switching energy and limited scalability. This work presents a time-domain CNN (TD-CNN) engine that achieves adaptive precision and computation reduction for ultralow-power operation. The main features include: 1) …

View on IEEE Xplore

Benchmarking of Emerging Material-Based TCAMs

Benchmarking of Emerging Material-Based TCAMs 150 150

Abstract:

This work presents a comprehensive benchmarking of ternary content-addressable memory (TCAM) implementations using timing-accurate SPICE simulations, systematically comparing conventional CMOS designs with emerging device technologies, including magnetic tunnel junctions (MTJs), ferroelectric tunnel junctions (FTJs), ferroelectric field-effect transistors (FeFETs), and 2-D reconfigurable field-effect transistors (2D RFETs). Key performance metrics, including search …

View on IEEE Xplore

A 10.1-ENOB 8kHz Bandwidth 95–250nW PVT-Robust DT Level-Crossing ADC for Sparse and Generic Signals

A 10.1-ENOB 8kHz Bandwidth 95–250nW PVT-Robust DT Level-Crossing ADC for Sparse and Generic Signals 150 150

Abstract:

This article presents an event-driven discrete-time level crossing analog-to-digital converter (DT-LCADC) that is energy-efficient in converting both sparse and generic signals and is robust against process voltage and temperature (PVT) variations. The proposed DT-LCADC uses the comparator delay to classify each level-crossing event as slow (produced by a small input …

View on IEEE Xplore