MS-ECE

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Revision as of 21:33, 3 March 2021 by Ted (talk | contribs) (Course Descriptions as of 2021)
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Determine terms available for some of the following courses:

CORE
ECE 540 System on a Chip Design with FPGAs
ECE 544 Embedded System Design with FPGAs
ECE 558 Embedded Systems Programming
EE 560 Foundations of Cyber-Physical Systems

Current students can complete the track with either ECE 585 or EE 560

DEPTH AND BREADTH COURSE LIST
ECE 525 Digital Integrated Circuit Design I
ECE 545 Power Electronics Systems Design I
ECE 551 Control Systems Design I
ECE 552 Control Systems Design II
ECE 571 Introduction to System Verilog for Design and Verification
ECE 578 Intelligent Robotics I
ECE 579 Intelligent Robotics II
ECE 581 ASIC Modeling and Synthesis
ECE 582 Formal Verification of HW/SW Systems
ECE 583 Low Power Digital IC Design
ECE 585 Microprocessor System Design
ECE 586 Computer Architecture
ECE 587 Advanced Computer Architecture I
ECE 588 Advanced Computer Architecture II
EE 519 Deep Learning Theory and Practice
EE 521 Mathematical Foundations of Machine Learning


Informal planning and scheduling

ECE 525 -- DIGITAL INTEGRATED CIRCUIT DESIGN I

| ECE 525 offered                           Fall  Winter           |
|                                             D     D              |
|                                             N     N              |  prereq's ECE 321 and STAT 351

ECE 540 -- SYSTEM-ON-CHIP DESIGN WITH FPGAS

| ECE 540 offered                           Fall  Winter           |
|                                             D     D              |
|                                             N                    |

no prerequisites listed

ECE 544 -- Embedded System Design with FPGAs

| ECE 544 offered                           Fall  Winter  Spring   |
|                                                            D     |
|                                                            N     |

ECE 558 -- Embedded Systems Programming

| ECE 558 offered                           Fall  Winter  Spring   |
|                                                   ?              |
|                                                   N              |

Prerequisite ECE 485 or ECE 585. Expected preparation: CS 202 and/or experience with Object-Oriented programming and Java.

EE 560 -- FOUNDATIONS OF CYBER-PHYSICAL SYSTEMS

| EE 560 offered                            Fall  Winter  Spring   |
|                                                            D     |
|                                                                  |

ECE 571 -- INTRODUCTION TO SYSTEM VERILOG FOR DESIGN AND VERIFICATION

| EE 560 offered                            Fall  Winter  Spring   |
|                                             D     D              |
|                                             N     N              |


Course Descriptions as of 2021

Some detailed course descriptions noted here:

Introduction to System Verilog for Design and Verification
ECE 571
Department: Elect and Computer Engineer
Description
Introduction to SystemVerilog:

 language features to support both design and verification.
 Good practices for simulation and synthesis, techniques for constructing reusable
 testbenches.   Additional topics may include hardware acceleration and transaction-based
 verification techniques. Course includes homework and significant final project with
 presentation. Familiarity with Verilog and finite state machines required.

 Prerequisites: One of following: ECE 351, ECE 540, ECE 544 or
   ECE 508: Verilog Workshop, or permission of instructor


ECE 581 - ASIC Modeling and Synthesis

ASIC: Modeling and Synthesis
ECE 581
Department: Elect and Computer Engineer
Description
 Covers the fundamentals of the ASIC design process. The topics include ASIC design Flow,
 basic HDL constructs, test benches, modeling combinational and synchronous logic,
 modeling finite state machines, multiple clock domain designs, qualitative design
 issues, ASIC constructions.

 Prerequisites: ECE 371.


ECE 586, first of three term series:

Computer Architecture
ECE 586
Department: Elect and Computer Engineer
Description
An introduction to the key concepts of computer system architecture and design. Topics
 include the design and analysis of instruction set architectures, memory systems, and
 high-performance IO systems; basic CPU implementation strategies; basic pipelined CPU
 implementation; performance analysis; and a survey of current architectures.

 Prerequisite: ECE 485/585.


^ Full Program course selection work

Full program course selection, tentative:

CORE
  [x] ECE 540 System on a Chip Design with FPGAs     2021-2022  -     -    FAL dn WIN d.
  [x] ECE 544 Embedded System Design with FPGAs      2021-2022 SPR dn -     -      -      also in 2022-2023, ECE 540 is prereq'
  [x] ECE 558 Embedded Systems Programming           2021-2022  -     -     -     WIN .n
  [x] EE 560 Foundations of Cyber-Physical Systems   2021-2022 SPR d. -     -      -

Current students can complete the track with either ECE 585 or EE 560

DEPTH AND BREADTH COURSE LIST
  [ ] ECE 525 Digital Integrated Circuit Design I
  [ ] ECE 545 Power Electronics Systems Design I
  [ ] ECE 551 Control Systems Design I
  [ ] ECE 552 Control Systems Design II
  [x] ECE 571 Introduction to System Verilog for Design and Verification  2021-2022  --- --  --- --  FAL dn  WIN dn
  [ ] ECE 578 Intelligent Robotics I
  [ ] ECE 579 Intelligent Robotics II

  [x] ECE 581 ASIC Modeling and Synthesis . . . . . . . . . . . . . . . . 2021-2022  --- --  --- --  FAL d-  WIN dn
  [x] ECE 582 Formal Verification of HW/SW Systems
  [x] ECE 583 Low Power Digital IC Design
  [x] ECE 585 Microprocessor System Design                                2021-2022  --- --  --- --  FAL d-  WIN dn
  [p] ECE 586 Computer Architecture                                       2021-2022  SPR d-  --- --  --- --  WIN dn   585 is prereq
  [ ] ECE 587 Advanced Computer Architecture I
  [ ] ECE 588 Advanced Computer Architecture II

  [x] EE 519 Deep Learning Theory and Practice                            NOT FOUND!
  [x] EE 521 Mathematical Foundations of Machine Learning                 NOT FOUND!

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