This course hence aims to equip students with core knowledge of multicore processor architectures and parallel computing, they will:
- understand where is the parallelism come from based on the advances in superscalar hyperthreading hardware architectures (multicore CPUs and GPUs);
- learn how to architect algorithms, software and solutions that can take full advantage of the latest hardware architectures;
- understand the principles of how to design correct and efficient parallel computing software and get familiar with the tools to debug and instrument parallel computing;
- get hands-on experience from case studies of algorithms/systems and readings from the current literature provide comparisons and contrasts.
- 50.004 Algorithms. Knowledge of Java/C programming is strongly encouraged.
- Explain the key technologies (e.g., pipeline, out-of-order execution, speculation) used in processor architecture for improving performance.
- Learning key concepts in design issues of multi-core processors, such as memory, communication, and scheduling.
- Learning how one can develop software that exploits parallelism and concurrency for efficiency, including using software libraries, tools, and formal techniques for design and benchmarking.
- Able to develop parallel computing algorithm or system component on modern multicore hardware architectures.
- Able to understand the fundamental concepts of multicore architectures [Exam].
- Implement a working efficient parallel computing algorithm/system components on modern multicore architectures [Projects].
- Implement, optimize and test parallel algorithms and data structures [Projects, Exams].
The overall module contains three parts.
- The first (week 1 ~ week 3) will focus on “what is parallel computing”, and “how to parallel computing”
- The second (week 4 ~ week 9) discuss “what are the potential problems in parallel computing and how to address them”, and “what are the common strategies to optimize parallel computing”
- The third (week 10 ~ week 12) will focus on advanced topics including “GPGPU programming”, “shared-nothing parallel computing”, “energy-efficient computing”.
- In the 13th week, we will have a summary and recap session to help students to fully digest the knowledges.
Textbooks & Required Readings
- Java Concurrency in Practice by Brian Goetz / Tim Peierls / Joshua Bloch / Joseph Bowbeer / David Holmes / Doug Lea, 2006
- Parallel Programming: For Multicore and Cluster Systems Authors: Rauber, Thomas, Rünger, Gudula
Recommended Texts and Readings
- Concurrency: State Models and Java Programming by Jeff Magee and Jeff Kramer, Wiley Second Edition.