This paper presents the analysis and design of a 26-39.5GHz power amplifier. In order to achieve high output power, we adopt the two-path voltage-combined topology. A voltage-mode power combiner is designed using stro...
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Longest Prefix Matching (LPM) plays an important role in fast IP processing. In this paper, a hardware coprocessor architecture connected to high-performance RISC-V processor is proposed to achieve faster LPM search. ...
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Learning from a few unseen samples to generalize the feature of new classes is a key challenge for real-time machine intelligence. To resolve this issue, the memory-augmented neural network (MANN) is proposed with an ...
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Advanced Driver Assistance systems (ADAS) has changed our lives in the field of automobile driving. Radar based automotive systems play an important role in increasing comfort and safety. This paper presents a stimula...
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This study focuses on the analytical modelling of a hybrid reluctance motor (HRM). For the first time, the nonlinear factors of magnetic leakage, fringing flux, and magnetic saturation in the HRM are all considered in...
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Constant False Alarm Rate (CFAR) is one of the key technologies for radar target detection, which can maintain a certain probability of false alarm during target detection. However, traditional CFAR algorithms only pe...
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The transimpedance amplifier (TIA) is a key component in the analog baseband (BB) of a current-mode receiver (RX). It requires low input impedance (Zin) and high linearity up to very high frequencies. However, due to ...
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This article presents a high-power wideband power amplifier (PA) with a four-way power-combining technique for $D$ -band high-resolution radar. The power combiner is based on a two-section Chebyshev impedance converte...
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An adaptive on-time (AOT) buck converter with constant switching frequency and fast transient response is presented. A frequency-locked loop (FLL) is used to achieve constant switching frequency. The on-time (TON) is ...
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Coarse-Grained Reconfigurable Arrays (CGRAs) are attracting more and more attention for their high flexibility and energy efficiency. Due to the limited resources, mapping large data flow graphs (DFGs) that represent ...
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ISBN:
(数字)9798350362190
ISBN:
(纸本)9798350362206
Coarse-Grained Reconfigurable Arrays (CGRAs) are attracting more and more attention for their high flexibility and energy efficiency. Due to the limited resources, mapping large data flow graphs (DFGs) that represent application kernels onto a CGRA is difficult, for which partitioning is employed. However, existing partitioning methods in the CGRA domain are unable to solve large kernels. In this work, we propose BOPart, an efficient DFG partitioning method based on Bayesian optimization. This enables the mapping of large DFGs that surpass the capacity of the target CGRA. Moreover, we design a graph coarsening method to reduce the complexity of the partitioning problem, which further improves the performance and convergence of BOPart. BOPart can handle benchmarks with up to 333 operations, surpassing the capability of state-of-the-art temporal mapping and partitioning method, which can only handle benchmarks with up to 94 operations.
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