Skip to main navigation Skip to search Skip to main content

Pivots: Bridge for Non-STEM Professionals into Application-Specific Integrated Circuit Design

Project: Research

Abstract & Details

Description

Award ID: 2347233

Computer chips and electronics are the vital backbone of our digital economy. As a strategic priority, the U.S. seeks to dramatically increase the domestic design of production of chips, which is currently being done offshore. Unfortunately, there is a talent gap between the projected job growth in this sector and available talent. The BASICS (Bridge to Application Specific Integrated Circuits) program seeks to provide non-STEM professionals with a self-paced, low-cost and fully-online curriculum to get a headstart in the chip design industry, culminating in a capstone project where students will fabricate and test their own small-sized chip. BASICS is a partnership between the successful BRIDGE program at New York University (NYU) that provides pathways for non-STEM professionals to computer science (CS) degrees and jobs, NYUs Computer Engineering department, and Zero-to-ASICs an online curriculum that teaches participants how to design their own chips. Graduating students will learn the basics of algorithms and programming, as well as theoretical foundations of chip design in addition to the chip design capstone. Once completed, the students will be eligible for direct admission to NYUs Masters in Computer Engineering program, and/or potential positions in the semiconductor industry. As Moores law flags, the semiconductor industry is looking towards application-specific integrated circuits (ASICs)chips specialized for specific tasks, for example, encryption, machine learning, etc.for continued innovation, unlocking orders-of-magnitude improvements in performance and energy efficiency. The skills required to fulfill these roles range from algorithms, software programming and scripting, to hardware design fundamentals and expertise in hardware description languages like Verilog, and are typically acquired in degree programs in Computer Engineering departments, but are out of reach for non-STEM professionals. Participants in the BASICS program will acquire each of these skills in a focused and online format: programming and algorithms from our existing BRIDGE program, hardware fundamentals including combinational and sequential circuit design from the Computer Engineering faculty, and hands-on knowledge on designing, synthesizing, floorplanning and taping out a chip from Zero-to-ASICs. The culmination is taping out and testing a small less than 1000 gate digital integrated circuit. Graduating students who enter the MS in Computer Engineering program at NYU or our partner institutions can then build on these skills via advanced classes from the transistor level to micro-architecture design, providing pathways to a range of roles in the semiconductor industry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Tyrslai Williams
StatusActive
Effective start/end date07/15/24 → 06/30/27

Funding

  • (ExLENT) Experiential Learning for Emerging and Novel Technologies : $1,000,000.00

Active Fiscal Year

  • FY2024
  • FY2027
  • FY2026
  • FY2025

Start Fiscal Year

  • FY2024

TIP Programs

  • (ExLENT) Experiential Learning for Emerging and Novel Technologies

Key Technology Areas

  • Advanced Computing and Semiconductors
  • (confidence score: 100%)

Technology Foci

  • Semiconductors
  • (confidence score: 100%)

Congressional District at Award

  • District n. 10 of New York

Current Congressional District

  • District n. 10 of New York

United States

  • New York

Core Based Statistical Area (CBSA)

  • New York-Newark-Jersey City, NY-NJ

County

  • County: New York, NY

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine