Freddy Gabbay
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View article: Predictive Maintenance System for Enhancing Chip Reliability and Resiliency in UxVs
Predictive Maintenance System for Enhancing Chip Reliability and Resiliency in UxVs Open
The emergence of Unmanned Vehicles (UxVs) has revolutionized various industries, offering unprecedented capabilities in areas such as surveillance, logistics, and environmental monitoring. As UxVs become increasingly integral to critical o…
View article: Hardware Design of DRAM Memory Prefetching Engine for General-Purpose GPUs
Hardware Design of DRAM Memory Prefetching Engine for General-Purpose GPUs Open
General-purpose graphics computing on processing units (GPGPUs) face significant performance limitations due to memory access latencies, particularly when traditional memory hierarchies and thread-switching mechanisms prove insufficient fo…
View article: The Effect of Asymmetric Transistor Aging on Systolic Arrays for Mission Critical Machine Learning Applications
The Effect of Asymmetric Transistor Aging on Systolic Arrays for Mission Critical Machine Learning Applications Open
Deep neural networks (DNNs) excel in various applications, such as computer vision, natural language processing, and other mission-critical systems. As the computational complexity of these models grows, there is an increasing need for spe…
View article: Teaching Experiences using the RVfpga Package
Teaching Experiences using the RVfpga Package Open
The RVfpga course offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-world RISC-V cores, the VeeR EH1 and the VeeR EL2, developed…
View article: Improving Weather Forecasts for Sailing Events Using a Combination of a Numerical Forecast Model and Machine Learning Postprocessing
Improving Weather Forecasts for Sailing Events Using a Combination of a Numerical Forecast Model and Machine Learning Postprocessing Open
Accurate predictions of wind and other weather phenomena are essential for making informed strategic and tactical decisions in sailing. Sailors worldwide utilize current state-of-the-art forecasts, yet such forecasts are often insufficient…
View article: Enhancing DNN Computational Efficiency via Decomposition and Approximation
Enhancing DNN Computational Efficiency via Decomposition and Approximation Open
The increasing computational demands of emerging deep neural networks (DNNs) are fueled by their extensive computation intensity across various tasks, placing a significant strain on resources. This paper introduces DART, an adaptive micro…
View article: The Impact of Asymmetric Transistor Aging on Clock Tree Design Considerations
The Impact of Asymmetric Transistor Aging on Clock Tree Design Considerations Open
Ensuring integrated circuits (ICs) operate reliably throughout their expected service life is more vital than ever, particularly as they become increasingly central to mission-critical applications. Advances in semiconductor technology hav…
View article: Electromigration-Aware Memory Hierarchy Architecture
Electromigration-Aware Memory Hierarchy Architecture Open
New mission-critical applications, such as autonomous vehicles and life-support systems, set a high bar for the reliability of modern microprocessors that operate in highly challenging conditions. However, while cutting-edge integrated cir…
View article: Electromigration-Aware Architecture for Modern Microprocessors
Electromigration-Aware Architecture for Modern Microprocessors Open
Reliability is a fundamental requirement in microprocessors that guarantees correct execution over their lifetimes. The reliability-related design rules depend on the process technology and device operating conditions. To meet reliability …
View article: Deep Neural Network Memory Performance and Throughput Modeling and Simulation Framework
Deep Neural Network Memory Performance and Throughput Modeling and Simulation Framework Open
Deep neural networks (DNNs) are widely used in various artificial intelligence applications and platforms, such as sensors in internet of things (IoT) devices, speech and image recognition in mobile systems, and web searching in data cente…
View article: Structured Compression of Convolutional Neural Networks for Specialized Tasks
Structured Compression of Convolutional Neural Networks for Specialized Tasks Open
Convolutional neural networks (CNNs) offer significant advantages when used in various image classification tasks and computer vision applications. CNNs are increasingly deployed in environments from edge and Internet of Things (IoT) devic…
View article: Computational Optimizations for Machine Learning
Computational Optimizations for Machine Learning Open
The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory …
View article: A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients
A LIME-Based Explainable Machine Learning Model for Predicting the Severity Level of COVID-19 Diagnosed Patients Open
The fast and seemingly uncontrollable spread of the novel coronavirus disease (COVID-19) poses great challenges to an already overloaded health system worldwide. It thus exemplifies an urgent need for fast and effective triage. Such triage…
View article: Compression of Neural Networks for Specialized Tasks via Value Locality
Compression of Neural Networks for Specialized Tasks via Value Locality Open
Convolutional Neural Networks (CNNs) are broadly used in numerous applications such as computer vision and image classification. Although CNN models deliver state-of-the-art accuracy, they require heavy computational resources that are not…
View article: Post-Training Sparsity-Aware Quantization
Post-Training Sparsity-Aware Quantization Open
Quantization is a technique used in deep neural networks (DNNs) to increase execution performance and hardware efficiency. Uniform post-training quantization (PTQ) methods are common, since they can be implemented efficiently in hardware a…
View article: Asymmetric aging effect on modern microprocessors
Asymmetric aging effect on modern microprocessors Open
Reliability is a crucial requirement in any modern microprocessor to assure correct execution over its lifetime. As mission critical components are becoming common in commodity systems; e.g., control of autonomous cars, the demand for reli…
View article: Early-Stage Neural Network Hardware Performance Analysis
Early-Stage Neural Network Hardware Performance Analysis Open
The demand for running NNs in embedded environments has increased significantly in recent years due to the significant success of convolutional neural network (CNN) approaches in various tasks, including image recognition and generation. T…
View article: Electromigration-Aware Architecture for Modern Microprocessors
Electromigration-Aware Architecture for Modern Microprocessors Open
Reliability is a fundamental requirement in any microprocessor to guarantee correct execution over its lifetime. The design rules related to reliability depend on the process technology being used and the expected operating conditions of t…