Results 31 to 40 of about 153 (43)
GraphGPT: Graph Instruction Tuning for Large Language Models
Graph Neural Networks (GNNs) have evolved to understand graph structures through recursive exchanges and aggregations among nodes. To enhance robustness, self-supervised learning (SSL) has become a vital tool for data augmentation.
Cheng, Suqi +7 more
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P2LSG: Powers-of-2 Low-Discrepancy Sequence Generator for Stochastic Computing
, 2023 Stochastic Computing (SC) is an unconventional computing paradigm processing data in the form of random bit-streams. The accuracy and energy efficiency of SC systems highly depend on the stochastic number generator (SNG) unit that converts the data from ...
Alam, Mohsen Riahi +3 more
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When arranged in a crossbar configuration, resistive memory devices can be used to execute MVM, the most dominant operation of many ML algorithms, in constant time complexity.
Ansaloni, Giovanni +8 more
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Rapid advancements in artificial intelligence have given rise to transformative models, profoundly impacting our lives. These models demand massive volumes of data to operate effectively, exacerbating the data-transfer bottleneck inherent in the ...
Imani, Mohsen +9 more
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Complete Boolean Algebra for Memristive and Spintronic Asymmetric Basis Logic Functions
The increasing advancement of emerging device technologies that provide alternative basis logic sets necessitates the exploration of innovative logic design automation methodologies.
Friedman, Joseph S., Vyas, Vaibhav
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NeuSpin: Design of a Reliable Edge Neuromorphic System Based on Spintronics for Green AI
Internet of Things (IoT) and smart wearable devices for personalized healthcare will require storing and computing ever-increasing amounts of data. The key requirements for these devices are ultra-low-power, high-processing capabilities, autonomy at low ...
Ahmed, Soyed Tuhin +4 more
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Exploring Liquid Neural Networks on Loihi-2
This study investigates the realm of liquid neural networks (LNNs) and their deployment on neuromorphic hardware platforms. It provides an in-depth analysis of Liquid State Machines (LSMs) and explores the adaptation of LNN architectures to neuromorphic ...
Dikmen, Ismail Can +3 more
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Adiabatic Quantum-Flux-Parametron (AQFP) logic is a promising emerging device technology that promises six orders of magnitude lower power than CMOS. However, AQFP is challenged by operation at only ultra-low temperatures, has high latency and area, and ...
Aviles, Robert S., Beerel, Peter A.
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Quantum Cloud Computing: A Review, Open Problems, and Future Directions
Quantum cloud computing is an emerging paradigm of computing that empowers quantum applications and their deployment on quantum computing resources without the need for a specialized environment to host and operate physical quantum computers.
Buyya, Rajkumar +4 more
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A key distinguishing feature of single flux quantum (SFQ) circuits is that each logic gate is clocked. This feature forces the introduction of path-balancing flip-flops to ensure proper synchronization of inputs at each gate.
Aviles, Robert S. +4 more
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