tag: Northeastern University

Chip Industry’s Technical Paper Roundup: Oct 18
By Linda Christensen - 18 Oct, 2022 - Comments: 0

New technical papers added to Semiconductor Engineering’s library this week. [table id=57 /] » read more

Highly Dense And Vertically Aligned Sub-5 nm Silicon Nanowires
By Technical Paper Link - 11 Oct, 2022 - Comments: 0

A new technical paper titled "Catalyst-free synthesis of sub-5 nm silicon nanowire arrays with massive lattice contraction and wide bandgap" was published by researchers at Northeastern University, Korea Institute of Science and Technology, Gyeongsang National University and others. "Here, we prepare highly dense and vertically aligned sub-5 nm silicon nanowires with length/diameter aspect r... » read more

Week In Review: Design, Low Power
By Jesse Allen - 16 Sep, 2022 - Comments: 0

Cadence unveiled a big data analytics infrastructure to unify massive data sets across all Cadence computational software. The Joint Enterprise Data and AI (JedAI) Platform aims to optimize multiple runs of multiple engines across an entire SoC design and verification flow. It combines data from its AI-driven Cerebrus implementation and Optimality system optimization solutions, along with the n... » read more

Technical Paper Round-Up: Aug 23
By Linda Christensen - 23 Aug, 2022 - Comments: 0

New technical papers added to Semiconductor Engineering’s library this week. [table id=46 /] Semiconductor Engineering is in the process of building this library of research papers. Please send suggestions (via comments section below) for what else you’d like us to incorporate. If you have research papers you are trying to promote, we will review them to see if they are a good fit for... » read more

Techniques For Improving Energy Efficiency of Training/Inference for NLP Applications, Including Power Capping & Energy-Aware Scheduling
By Technical Paper Link - 17 Aug, 2022 - Comments: 0

This new technical paper titled "Great Power, Great Responsibility: Recommendations for Reducing Energy for Training Language Models" is from researchers at MIT and Northeastern University. Abstract: "The energy requirements of current natural language processing models continue to grow at a rapid, unsustainable pace. Recent works highlighting this problem conclude there is an urgent need ... » read more

Technical Paper Round-Up: March 15
By Linda Christensen - 15 Mar, 2022 - Comments: 0

Research is expanding across a variety of semiconductor-related topics, from security to flexible substrates and chiplets. Unlike in the past, when work was confined to some of the largest universities, that research work is now being spread across a much broader spectrum of schools on a global basic, including joint research involving schools whose names rarely appeared together. Among the ... » read more

Mapping Transformation Enabled High-Performance and Low-Energy Memristor-Based DNNs
By Technical Paper Link - 14 Mar, 2022 - Comments: 0

Abstract: "When deep neural network (DNN) is extensively utilized for edge AI (Artificial Intelligence), for example, the Internet of things (IoT) and autonomous vehicles, it makes CMOS (Complementary Metal Oxide Semiconductor)-based conventional computers suffer from overly large computing loads. Memristor-based devices are emerging as an option to conduct computing in memory for DNNs to make... » read more

PTAuth: Temporal Memory Safety via Robust Points-to Authentication
By Technical Paper Link - 08 Sep, 2021 - Comments: 0

Authors: Reza Mirzazade Farkhani, Mansour Ahmadi, and Long Lu, Northeastern University Abstract: "Temporal memory corruptions are commonly exploited software vulnerabilities that can lead to powerful attacks. Despite significant progress made by decades of research on mitigation techniques, existing countermeasures fall short due to either limited coverage or overly high overhead. Further... » read more

FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator
By Technical Paper Link - 19 Aug, 2021 - Comments: 0

Abstract: "Recent work demonstrated the promise of using resistive random access memory (ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ matrix-vector multiplication—the intensive and key computation in deep neural networks (DNNs). One key problem is the weights that are signed values. However, in a ReRAM crossbar, weights are stored as conductance of... » read more

Manufacturing Bits: March 9
By Mark LaPedus - 09 Mar, 2020 - Comments: 0

Finding cures for coronavirus The Department of Energy’s Oak Ridge National Laboratory (ORNL) is using the world’s most powerful supercomputer to identify drug compounds and cures for the coronavirus. [caption id="attachment_24162601" align="alignleft" width="300"] Summit supercomputer. Source: Oak Ridge National Laboratory[/caption] The supercomputer, called Summit, has identified 7... » read more

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