Ph.D. Proposal Oral Exam - Siri Narla

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Event Details
  • Date/Time:
    • Friday February 3, 2023
      2:30 pm - 4:30 pm
  • Location: https://teams.microsoft.com/l/meetup-join/19%3ameeting_OGJlMzE1OTMtY2JkNS00MDg4LTg0ODUtMDRhMzU5Mjk2ZTA0%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%226beb7c73-d36f-4a90-a09c-77141bc15aa2%22%7d
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  • Fee(s):
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Contact
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Summaries

Summary Sentence: Context based search using Content Addressable Memory

Full Summary: No summary paragraph submitted.

Title:  Context based search using Content Addressable Memory

Committee: 

Dr. Naeemi, Advisor      

Dr. Mukhopadhyay, Chair

Dr. Romberg

Abstract: The objective of the proposed research is to design unconventional circuits to take advantage of non- volatile memories like Spin Orbit Torque (SOT) and Magnetoelectric (ME) Magnetic random access memory (MRAM). Content addressable memories (CAMs) have proved themselves to be worthy contenders for data-intensive applications. CAMs have been used in many applications for performing similarity and nearest neighbor search. However, challenges like minimum detectable Hamming distance, discharge current saturation and energy and performance efficiency have limited their use. In recommendation models and hyperdimensional computing, the features/bits important to a query while searching through the dataset change for each search cycle based on ’context’. Here we will propose SOT and ME-based CAM design to perform NNS with ’context’. This allows us to improve energy efficiency of CAMs and improves the quality of search.

Additional Information

In Campus Calendar
No
Groups

ECE Ph.D. Proposal Oral Exams

Invited Audience
Public
Categories
Other/Miscellaneous
Keywords
Phd proposal, graduate students
Status
  • Created By: Daniela Staiculescu
  • Workflow Status: Published
  • Created On: Jan 26, 2023 - 5:06am
  • Last Updated: Jan 26, 2023 - 5:06am