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Efficient Floating-Point SRAM Compute-in-Memory by Harnessing Mantissa Addition
In the era of machine learning, particularly in the context of compute-in-memory (CIM) systems, has been rapidly evolving to meet the escalating demands of high computational efficiency and energy conservation. Existing SRAM CIM approaches have often focused on either fully digital or analog domains, leading to trade-offs between accuracy and energy...
Published: 7/30/2024   |   Inventor(s): Weidong Cao
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Category(s): Technology Classifications > Computers Electronics & Software, Technology Classifications > Computers Electronics & Software > Processing Chips, Technology Classifications > Computers Electronics & Software > Artificial Intelligence, Technology Classifications > Computers Electronics & Software > Cloud Computing, Technology Classifications > Computers Electronics & Software > Databases
SAM: Spintronic Approximate Memory
In the ever-evolving landscape of artificial intelligence (AI), achieving power efficiency without sacrificing accuracy has been a perennial challenge. Traditional methods, such as low supply voltage SRAM and low refresh rate DRAM, have aimed to reduce power consumption but have fallen short due to their lack of bitwise control over memory accuracy....
Published: 7/30/2024   |   Inventor(s): Abdolah Amirany, Tarek El-Ghazawi, Hamidreza Imani Porshokouh
Keywords(s):  
Category(s): Technology Classifications, Technology Classifications > Computers Electronics & Software > Artificial Intelligence, Technology Classifications > Computers Electronics & Software > Computing Architecture, Technology Classifications > Computers Electronics & Software > Processing Chips, Technology Classifications > Computers Electronics & Software > Databases
Conditional Variational Autoencoder for Functional Connectivity Analysis of ASD fMRI Data: A Comparative Study
Autism Spectrum Disorder (ASD), a complex neurodevelopmental condition, has been a subject of extensive research and clinical investigation due to its diverse manifestations and challenging diagnostic criteria. Existing methods for analyzing functional MRI (fMRI) data, particularly in the context of autism spectrum disorder (ASD), have faced significant...
Published: 7/30/2024   |   Inventor(s): Mariia Sidulova, Chung Hyuk Park
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Category(s): Technology Classifications > Computers Electronics & Software > Sensors, Technology Classifications > Computers Electronics & Software > Artificial Intelligence, Technology Classifications > Computers Electronics & Software, Technology Classifications > Computers Electronics & Software > Image Processing and Analysis, Technology Classifications > Medical Devices > Neurostimulation
SPACX: A Hardware and Algorithm Co-Optimized Photonic Deep Neural Network Computing Architecture
SPACX- A silicon-based Photonic accelerator for DNN Chiplets architecture The continuous increase in size and complexity of deep neural network (DNN) models leads to rapidly increasing demand for computing capacity which has outpaced the scaling capability of conventional monolithic chips. Chiplet-based DNN accelerators have emerged as a promising...
Published: 7/30/2024   |   Inventor(s): Yuan Li, Ahmed Louri
Keywords(s):  
Category(s): Technology Classifications, Technology Classifications > Computers Electronics & Software, Technology Classifications > Computers Electronics & Software > Artificial Intelligence, Technology Classifications > Computers Electronics & Software > Processing Chips, Technology Classifications > Computers Electronics & Software > Computing Architecture
Symmetry-Detecting Spiking Artificial Neural Network
Researchers at GW have developed a novel and efficient solution to detect symmetry lines and points within multidimensional spatial data that could be utilized in data processing and robotics. The solution can take the form of one or more artificial neural networks that can be configured to efficiently detect symmetry lines and points within multidimensional...
Published: 7/30/2024   |   Inventor(s): Jonathan George, Volker Sorger
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Category(s): Technology Classifications > Computers Electronics & Software > Cloud Computing, Technology Classifications > Computers Electronics & Software > Computing Architecture, Technology Classifications > Computers Electronics & Software > Robotics, Technology Classifications > Computers Electronics & Software > Artificial Intelligence
Residue Number System Adder and Multiplier based on Integrated Nanophotonics
Researchers at GW have developed a novel, cost-effective, and energy-efficient residue number system (RNS) adder and multiplier that is based on integrated nanophotonics. The disclosed invention utilizes multiplication-accumulation computation (MAC) operations that can use one summand/multiplicand repetitively millions of times. In other words, aspects...
Published: 7/30/2024   |   Inventor(s): Volker Sorger, Tarek El-Ghazawi, Shuai Sun, Jiaxin Peng
Keywords(s):  
Category(s): Technology Classifications > Computers Electronics & Software > Cloud Computing, Technology Classifications > Computers Electronics & Software > Artificial Intelligence
A Hardware-based Cyber-deception Framework to Combat Malware
Researchers at GW have developed a hardware-based cyber-deception framework that can effectively combat malware directed to attacking computer systems. In particular, the framework works deceptively and transparently, to modify the underlying malware during program runtime and strategically deflects the malware from accessing sensitive information associated...
Published: 7/30/2024   |   Inventor(s): Guru Venkataramani, Preet Derasari, Kailash Gogineni
Keywords(s):  
Category(s): Technology Classifications > Computers Electronics & Software > Artificial Intelligence, Technology Classifications > Computers Electronics & Software > Computing Architecture, Technology Classifications > Computers Electronics & Software > Cybersecurity
Schematic Operation of On-line Update Matrix Decomposer Architecture for Machine Learning Hardware
Researchers at GW have developed an effective, improved, and cost-effective training acceleration solution that is novel, for large scale neural networks in the field of Artificial Intelligence. The novel solution can also be implemented in a variety of hardware applications that is associated with training acceleration in machine learning as can be...
Published: 7/30/2024   |   Inventor(s): Gina Adam
Keywords(s):  
Category(s): Technology Classifications > Computers Electronics & Software > Artificial Intelligence, Technology Classifications > Computers Electronics & Software > Computing Architecture
A Flexible and Energy-Efficient Accelerator for Graph Convolutional Neural Networks
Researchers at GW have invented a flexible and energy-efficient accelerator for graph convolutional neural networks (GCN). First, the novel accelerator design disclosed shows highly enhanced performance in comparison to existing accelerators. For example, the accelerator is capable of simultaneously improving resource utilization and data movement in...
Published: 7/30/2024   |   Inventor(s): Ahmed Louri, Jiajun Li
Keywords(s):  
Category(s): Technology Classifications > Computers Electronics & Software > Artificial Intelligence, Technology Classifications > Computers Electronics & Software > Computing Architecture
An Algorithm-Hardware Co-design Method for Convolutional Neural Networks
Researchers at GW have developed an algorithm-hardware co-design framework for Convolutional Neural Networks (CNN) directed towards mitigating the effects of computational irregularities in existing models. The framework disclosed allows for a reduced model size as to the associated system. For example, the algorithm disclosed utilizes centrosymmetric...
Published: 7/30/2024   |   Inventor(s): Jiajun Li, Ahmed Louri
Keywords(s):  
Category(s): Technology Classifications > Computers Electronics & Software > Computing Architecture, Technology Classifications > Computers Electronics & Software > Artificial Intelligence