Academics / Graduate Study / MS Programs / Master of Science in Computer Engineering High-Performance Computing Specialization
The enormous growth in artificial intelligence (AI) and Internet of Things (IoT) is fueling a growing demand for high-efficiency computing to perform real-time analysis on massive amounts of data. In many industries, large clusters of servers must work together in parallel to complete tasks faster.
High-performance computing (HPC) refers to the practice of aggregating computing resources into clusters that can analyze huge volumes of data in parallel, and process calculations at speeds far exceeding what is possible using traditional computing. This is crucial for today’s businesses, institutions, and researchers, who are turning to HPC to solve large, complex, performance-intensive problems in far less time, with higher accuracy, and at a lower cost than traditional methods. For example, medical researchers are using HPC to speed up time to develop vaccines, screen for diseases, and provide more accurate patient diagnoses. Financial institutions are using HPC to automate trading, analyze market trends, and detect credit card fraud. Media businesses are using HPC to stream live events, produce special effects, edit films, and create immersive entertainment. The ability to process large volumes of data at high speeds is prompting businesses in financial, energy, healthcare, retail, and manufacturing to adopt these HPC systems to solve some of the world’s biggest problems.
With the rapid growth of multi-core processors, GPUs, hardware accelerators, and networked computing platforms, HPC is becoming more ubiquitous and easily accessible. With cloud computing, HPC infrastructure can now be procured and deployed faster and at any given moment. In this track, you will gain the necessary skills in all aspects of high-performance computing to meet the needs of this rising industry, including parallel programming, computer architecture, and distributed computing.
Recommended Courses
Core Courses
Select at least six courses from the following list:
- CE 303 Advanced Digital Design
- CE 329 The Art of Multicore Concurrent Programming
- CE 355 ASIC and FPGA Design
- CE 358 Intro to Parallel Computing
- CE 361 Computer Architecture I
- CE 368, 468 Programming Massively Parallel Processors with CUDA
- CE 392 VLSI Systems Design Projects
- CE 395, 495 Advanced Digital System Design with FPGAS
- CE 453 Parallel Architectures
- CS 322 Compiler Construction
- CS 323 Code Analysis and Transformation
- CS 397, 497 Advanced Topics in Compilers
Elective Courses
Select up to six courses from the following list:
- CE 362 Computer Architecture Project
- CE 510 Social Media Mining
- CS 345 Distributed Systems
- EE 326 Electronic System Design I
- EE 327 Electronic System Design II
- EE 375, 475 Machine Learning: Foundations, Applications, and Algorithms
- EE 395, 495 Introduction to Smart Grid Systems
- EE 424 Distributed Optimization
- EE 435 Deep Learning Foundations from Scratch
