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Analog/digital hybrid precoder and combiner have been widely used in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems due to its energy-efficient and economic superiorities. Infinite resolution of phase shifters (PSs)…
Printed electronics have gained significant traction in recent years, presenting a viable path to integrating computing into everyday items, from disposable products to low-cost healthcare. However, the adoption of computing in these…
In this paper, two approximate 3*3 multipliers are proposed and the synthesis results of the ASAP-7nm process library justify that they can reduce the area by 31.38% and 36.17%, and the power consumption by 36.73% and 35.66% compared with…
Multiplication is an important arithmetic operation that is frequently encountered in microprocessing and digital signal processing applications, and multiplication is physically realized using a multiplier. This paper discusses the…
In this paper, we propose FusionCIM, an operator-fusion-driven compute-in-memory (CIM) accelerator architecture for efficient and scalable LLM inference, with three key innovations: (1) a hybrid CIM pipeline architecture that maps QKT…
In our previous work [2], we introduced a hardware- and power-efficient architecture for hybrid digital-analog (HDA) multiuser MIMO (MU-MIMO) based on stacking identical basic modules. Each module consists of a small active multi-antenna…
Navigating rigid body objects through crowded environments can be challenging, especially when narrow passages are presented. Existing sampling-based planners and optimization-based methods like mixed integer linear programming (MILP)…
Chiplet architectures are on the rise as they promise to overcome the scaling challenges of monolithic chips. A key component of such architectures is an efficient inter-chiplet interconnect (ICI). The ICI design space is huge as there are…
This paper proposes four quadrant analog multiplier using CMOS-memristor circuit. Currently, there are plenty of analog multipliers using resistors and CMOS transistors. They can attain perfect multiplication but have several disadvantages…
Monolithic 3D integration has become a promising solution for future computing needs. The metal inter-layer via (MIV) forms interconnects between substrate layers in Monolithic 3D integration. Despite small size of MIV, the area overhead…
The paper presents a systematic study and implementation of a reconfigurable combinatorial multi-operand adder for use in Deep Learning systems. The size of carry changes with the number of operands and hence a reliable algorithm to…
Computing-in-Memory (CIM) architectures have emerged as a promising solution for accelerating Deep Neural Networks (DNNs) by mitigating data movement bottlenecks. However, realizing the potential of CIM requires specialized dataflow…
Edge computing is emerging as a new paradigm to allow processing data at the edge of the network, where data is typically generated and collected, by exploiting multiple devices at the edge collectively. However, exploiting the potential of…
A 28nm dense 6T-SRAM Digital(D)/Analog(A) Hybrid compute-in-memory (CIM) macro supporting complex num-ber MAC operation is presented. By introducing a 2D-weighted Capacitor Array, a hybrid configuration is adopted where digital CIM is…
Computing-in-Memory (CIM) macros have gained popularity for deep learning acceleration due to their highly parallel computation and low power consumption. However, limited macro size and ADC precision introduce throughput and accuracy…
A switched-capacitor matrix multiplier is presented for approximate computing and machine learning applications. The multiply-and-accumulate operations perform discrete-time charge-domain signal processing using passive switches and 300 aF…
The Mixture-of-Experts (MoE) models have emerged as the state-of-the-art paradigm for scaling up large language models (LLMs) without proportionally increased computational cost. However, its on-device deployment faces a critical challenge…
Memory load/store instructions consume an important part in execution time and energy consumption in domain-specific accelerators. For designing highly parallel systems, available parallelism at each granularity is extracted from the…
Matrix multiplication (GEMM) is a core operation to numerous scientific applications. Traditional implementations of Strassen-like fast matrix multiplication (FMM) algorithms often do not perform well except for very large matrix sizes, due…
In this paper, we focus on large intelligent reflecting surfaces (IRSs) and propose a new codebook construction method to obtain a set of pre-designed phase-shift configurations for the IRS unit cells. Since the complexity of online…