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ECE 786 Advanced Computer Architecture: Data Parallel Processors

3 Credit Hours

In-depth study of processor architectures to exploit data-level parallelism, including general computation on graphics processing units (GPGPU, aka GPU computing architecture) and vector processors; memory subsystems; advantages and disadvantages of various architectures; technology shifts, trends, and constraints. Students undertake major course projects.

Prerequisite

Instruction set architecture, Pipelined processor architecture, caches, and C++ programming.

Course Requirements

The course requirement includes:

~4 Homeworks

~2 CUDA Programming Assignments

2 Exams (Midterm and Final)

1 Term Project

Course Topics

Introduction, Background, and Overview (1 week)

Vector Processors (1 week)

General Purpose Computation on Graphics Processing Units (GPGPU) aka SIMT Processors (7 weeks)

  • 3.1 Programming Model & System Architecture (1 week)
  • 3.2 Microarchitecture (3 weeks)
  • 3.3 Memory Subsystem (1.5 week)
  • 3.4 Performance Analysis (1.5 week)

Research Topics on GPUs and Vector Processors & Research Paper Presentation (5.5 weeks)

Midterm and Final Exams (1 week)

Textbook

None

Updated: 10/31/2022