Fall 2023
Tue, Thu
3:00-04:15 PM
LSB 231
Mon-Wed 10-11AM (Zoom)
This course is an introduction to high-performance computing. High-performance computing (HPC) is the practice of leveraging parallel computing power, from computer clusters and supercomputers, to solve complex computational problems faster. In this course students will learn the main programming models, such as openMP and MPI, to write highly optimized code for modern multi-core processors, clusters, and modern computing architecture (e.g., GPUs). Furthermore, this course will explore the concepts and challenges of performance scalability, portability, and energy efficiency of HPC applications and systems.
Lecturer: Dr. Steve Petruzza TA: Andres Sewell
Topics include: multithread programming, openMP, distributed programming, MPI, performance profiling, parallel and distributed algorithms, parallel I/O, in situ analytics, GPU programming.
Prerequisites: a good C/C++ programming background. Most of the assignment will be in C/C++. In particular, a student needs to have knowledge of data structures, arrays, pointers and memory allocation in C/C++. If you are not too familiar with C/C++ here is a tutorial that could be useful, the “C++ basic” section is a good place to start. If you are not familiar with the Unix terminal:
Day | Topic | References | Homework |
---|---|---|---|
Aug 29 | Introduction | IPP Ch. 1 | |
Aug 31 | Computing architecture and memory | IPP Ch. 2 | |
Sep 5 | Parallel hardware and interconnects | IPP Ch. 2 | |
Sep 7 | Parallel software and scalability | IPP Ch. 2 | HW1 |
Sep 12 | Parallel software and scalability (2) | IPP Ch. 4 | |
Sep 14 | Shared memory programming: PThreads | IPP Ch. 4 | |
Sep 19 | C++11 Threads and running on an HPC system | CHPC | |
Sep 21 | Shared memory programming: PThreads (2) | IPP Ch. 4 | |
Sep 26 | OpenMP (1) | IPP Ch. 5 | HW2 |
Sep 28 | OpenMP (2) | IPP Ch. 5 | |
Oct 3 | OpenMP (3) | IPP Ch. 5 | |
Oct 5 | Distributed programming: basics | IPP Ch. 3 | HW3 |
Oct 10 | Distributed programming: MPI | IPP Ch. 3 | |
Oct 12 | MPI Parallel I/O | IPP Ch. 3 | |
Oct 17 | Mid-term exam | ||
Oct 19 | No class | HW4 | |
Oct 24 | MPI (2) | IPP Ch. 3 | |
Oct 26 | MPI | IPP Ch. 3 | |
Oct 31 | Introduction to GPU Programming and CUDA | GPU Ch.1,2,3 | |
Nov 2 | Review and GPU programming (2) | GPU Ch. 4 | |
Nov 7 | GPU: execution model | GPU Ch. 5 | |
Nov 9 | GPU: memory model and tiling | GPU Ch. 6,7 | HW5 |
Nov 14 | GPU: convolution | GPU Ch. 8 | |
Nov 16 | GPU: convolution analysis | ||
Nov 21 | Project workgroups | HW6 | |
Nov 23 | Thanksgiving | ||
Nov 28 | Python for HPC | ||
Nov 30 | Performance Profiling | ||
Dec 5 | Project workgroups | ||
Dec 7 | Review and Project presentations | ||
Dec 12 | Finals | ||
Dec 14 | Finals |
The date in the “Homework” column represents when the homework is assigned. Homework are generally due after one or two weeks. The schedule above is subject to change.
Selection/proposal deadline: TBD
Submission deadline: TBD
A [93%, 100%] A- [90%, 93%) B+ [90%, 87%) B [87%, 83%) B- [83%, 80%) C+ [80%, 77%) C [77%, 73%) C- [73%, 70%) D+ [70%, 67%) D [67%, 60%) F Below 59%
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