10 citations · 10 across the 2 of their papers we have counts for
8 papers
FlexWatts: A Power- and Workload-Aware Hybrid Power Delivery Network for Energy-Efficient Microprocessors
Jawad Haj-Yahya, Mohammed Alser, Jeremie S. Kim +5
Modern client processors typically use one of three commonly-used power delivery network (PDN): 1) motherboard voltage regulators (MBVR), 2) integrated voltage regulators (IVR), an…
Asymmetric Aging Effect on Modern Microprocessors
Freddy Gabbay, Avi Mendelson
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 sys…
Colored Noise Injection for Training Adversarially Robust Neural Networks
Evgenii Zheltonozhskii, Chaim Baskin, Yaniv Nemcovsky +3
Even though deep learning has shown unmatched performance on various tasks, neural networks have been shown to be vulnerable to small adversarial perturbations of the input that le…
Smoothed Inference for Adversarially-Trained Models
Yaniv Nemcovsky, Evgenii Zheltonozhskii, Chaim Baskin +4
Deep neural networks are known to be vulnerable to adversarial attacks. Current methods of defense from such attacks are based on either implicit or explicit regularization, e.g.,…
Loss Aware Post-training Quantization
Yury Nahshan, Brian Chmiel, Chaim Baskin +4
Neural network quantization enables the deployment of large models on resource-constrained devices. Current post-training quantization methods fall short in terms of accuracy for I…
CAT: Compression-Aware Training for bandwidth reduction
Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii +3
Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving visual processing tasks. One of the major obstacles hindering the ubiquitous u…