Search Results - "2020 IEEE 38th International Conference on Computer Design (ICCD)"

NATSA: A Near-Data Processing Accelerator for Time Series Analysis by Fernandez, Ivan, Quislant, Ricardo, Gutierrez, Eladio, Plata, Oscar, Giannoula, Christina, Alser, Mohammed, Gomez-Luna, Juan, Mutlu, Onur

“…Time series analysis is a key technique for extracting and predicting events in domains as diverse as epidemiology, genomics, neuroscience, environmental…”
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OpenCGRA: An Open-Source Unified Framework for Modeling, Testing, and Evaluating CGRAs by Tan, Cheng, Xie, Chenhao, Li, Ang, Barker, Kevin J., Tumeo, Antonino

“…Coarse-grained reconfigurable arrays (CGRAs), loosely defined as arrays of functional units (e.g., adder, subtractor, multiplier, divider, or larger…”
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Phased-Guard: Multi-Phase Machine Learning Framework for Detection and Identification of Zero-Day Microarchitectural Side-Channel Attacks by Wang, Han, Sayadi, Hossein, Kolhe, Gaurav, Sasan, Avesta, Rafatirad, Setareh, Homayoun, Houman

“…Microarchitectural Side-Channel Attacks (SCAs) have emerged recently to compromise the security of computer systems by exploiting the existing processors'…”
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4-output Programmable Spin Wave Logic Gate by Mahmoud, Abdulqader, Vanderveken, Frederic, Adelmann, Christoph, Ciubotaru, Florin, Hamdioui, Said, Cotofana, Sorin

“…To bring Spin Wave (SW) based computing paradigm into practice and develop ultra low power Magnonic circuits and computation platforms, one needs basic logic…”
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Learn to Floorplan through Acquisition of Effective Local Search Heuristics by He, Zhuolun, Ma, Yuzhe, Zhang, Lu, Liao, Peiyu, Wong, Ngai, Yu, Bei, Wong, Martin D.F.

“…Automatic heuristic design through reinforcement learning opens a promising direction for solving computationally difficult problems. Unlike most previous…”
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BranchSpec: Information Leakage Attacks Exploiting Speculative Branch Instruction Executions by Islam Chowdhuryy, Md Hafizul, Liu, Hang, Yao, Fan

“…Recent studies on attacks exploiting processor hardware vulnerabilities have raised significant concern for information security. Particularly, transient…”
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EM-GAN: Data-Driven Fast Stress Analysis for Multi-Segment Interconnects by Jin, Wentian, Sadiqbatcha, Sheriff, Sun, Zeyu, Zhou, Han, Tan, Sheldon X.-D.

“…Electromigration (EM) analysis for complicated interconnects requires the solving of partial differential equations, which is expensive. In this paper, we…”
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Hardware-Assisted Malware Detection using Explainable Machine Learning by Pan, Zhixin, Sheldon, Jennifer, Mishra, Prabhat

“…Malicious software, popularly known as malware, is widely acknowledged as a serious threat to modern computing systems. Software-based solutions, such as…”
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Special Session: Noninvasive Sensor-Spoofing Attacks on Embedded and Cyber-Physical Systems by Barua, Anomadarshi, Al Faruque, Mohammad Abdullah

“…Recent decades have observed the proliferation of sensors in embedded and cyber-physical systems (ECPSs). Sensors are an essential part of embedded and CPSs…”
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CMSA: Configurable Multi-directional Systolic Array for Convolutional Neural Networks by Xu, Rui, Ma, Sheng, Wang, Yaohua, Guo, Yang

“…The systolic array is one of the most popular choices for convolutional neural network accelerators. However, when computing special convolution, such as…”
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Chain-Based Fixed-Priority Scheduling of Loosely-Dependent Tasks by Choi, Hyunjong, Karimi, Mohsen, Kim, Hyoseung

“…Many cyber-physical applications consist of chains of tasks. Such tasks are often loosely dependent, meaning task execution is time-triggered and independent…”
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ND-HMDs: Non-Differentiable Hardware Malware Detectors against Evasive Transient Execution Attacks by Islam, Md Shohidul, Kuruvila, Abraham Peedikayil, Basu, Kanad, Khasawneh, Khaled N.

“…Transient execution attacks exploit performance optimizations, built into modern CPU designs, to leak sensitive data through side channels. Preventing such…”
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ASIC Accelerator in 28 nm for the Post-Quantum Digital Signature Scheme XMSS by Mohan, Prashanth, Wang, Wen, Jungk, Bernhard, Niederhagen, Ruben, Szefer, Jakub, Mai, Ken

“…This paper presents the first 28 nm ASIC implementation of an accelerator for the post-quantum digital signature scheme XMSS. In particular, this paper…”
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EdgeNAS: Discovering Efficient Neural Architectures for Edge Systems by Luo, Xiangzhong, Liu, Di, Kong, Hao, Liu, Weichen

“…Edge systems integrated with deep neural networks (DNNs) are deemed to pave the way for future artificial intelligence (AI). However, designing accurate and…”
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WoLFRaM: Enhancing Wear-Leveling and Fault Tolerance in Resistive Memories using Programmable Address Decoders by Yavits, Leonid, Orosa, Lois, Mahar, Suyash, Ferreira, Joao Dinis, Erez, Mattan, Ginosar, Ran, Mutlu, Onur

“…Resistive memories have limited lifetime caused by limited write endurance and highly non-uniform write access patterns. Two main techniques to mitigate…”
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Special Session: Noise Characterization and Error Mitigation in Near-Term Quantum Computers by Wood, Christopher J.

“…A detailed understanding of the noise processes and errors in near-term quantum computers is essential for accurate calibration of gates, and for achieving…”
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Re-Thinking Mixed-Criticality Architecture for Automotive Industry by Jiang, Zhe, Zhao, Shuai, Dong, Pan, Yang, Dawei, Wei, Ran, Guan, Nan, Audsley, Neil

“…Mixed-Criticality System (MCS) has been considered widely within academic literature, but is proving difficulty to implement in industry as the theoretical…”
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Special Session: Exploring the Ultimate Limits of Adiabatic Circuits by Frank, Michael P., Brocato, Robert W., Conte, Thomas M., Hsia, Alexander H., Jain, Anirudh, Missert, Nancy A., Shukla, Karpur, Tierney, Brian D.

“…The field of adiabatic circuits is rooted in electronics know-how stretching all the way back to the 1960s and has potential applications in vastly increasing…”
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Reconfigurable Dataflow Optimization for Spatiotemporal Spiking Neural Computation on Systolic Array Accelerators by Lee, Jeong-Jun, Li, Peng

“…Spiking neural networks (SNNs) offer a promising biologically-plausible computing model and lend themselves to ultra-low-power event-driven processing on…”
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Hardware-based Fast Real-time Image Classification with Stochastic Computing by Muthappa, Ponnanna Kelettira, Neugebauer, Florian, Polian, Ilia, Hayes, John P.

“…Stochastic computing (SC) with its small area and power footprint is a prime candidate for realizing neural networks (NNs) in heavily resource-restricted…”
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