數值軟體開發
Numerical Software Development
| 節 | 週一 |
|---|---|
Z 07:00–07:50 | 數值軟體開發 EC114 3 節連堂 |
1 08:00–08:50 | |
2 09:00–09:50 |
* 根據陽明交大上課時間表所列
The course introduces the art of building numerical software, i.e., computer programs applying numerical methods for solving mathematical, scientfic, or engineering problems. We will be using Python, C++ and other tools (e.g., bash, git, make, etc.) to learn the modern development processes. By completing this course, students will acquire the fundamental skills for developing modern numerical software. Course notes: https://yyc.solvcon.net/en/latest/nsd/ . Course schedule: https://yyc.solvcon.net/en/latest/nsd/schedule/22au_nycu/schedule.html .
Students should have taken computer architecture and engineering mathematics or equivalents. Working knowledge of Linux and Unix-like is required. Prior knowledge to numerical methods is recommended. The instructor uses English in the lectures and discussions.
The instructor will use English. It is OK for students to use Mandarin in the class, but English is preferred. Computer program for homework and project should be developed against the latest Ubuntu LTS system.
* You are expected to learn programming languages yourself. Python is easy, but C++ may be challenging. Students are encouraged to form study groups for practicing C++, and discuss with the instructor and/or the teaching assistant. * Grading: homework 30%, mid-term exam: 30%, term project: 40%. * There are 12 lectures for the subjects of numerical software developing using Python and C++. * There will be 6 homework assignments for you to exercise. Programming in Python and/or C++ is required. * Mid-term examination will be conducted to assess students' understandings to the analytical materials. * Term project will be used to assess students' overall coding skills. Presentation is required. Failure to present results in 0 point for this part.
- Introduction
- Fundamental engineering
- Python and numpy
- C++ and computer architecture
- Matrix operations
- Cache optimization
- SIMD (vector processing)
- Memory management
- Ownership and smart pointers
- Modern C++
- C++ and C for Python
- Array code in C++
- Advanced Python
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction (assignment #1) |
| 第 2 週 | Unit 1: Fundamental Engineering (proposal open) |
| 第 3 週 | Unit 2: Python and Numpy |
| 第 4 週 | Unit 3: C++ and Computer Architecture (assignment #2) |
| 第 5 週 | No meeting (national day) |
| 第 6 週 | Unit 4: Matrix Operations |
| 第 7 週 | Unit 5: Cache Optimization (assignment #3) |
| 第 8 週 | Unit 6: SIMD (Vector Processing) (proposal due) |
| 第 9 週 | Mid-term examination |
| 第 10 週 | Unit 7: Memory Management (assignment #4) |
| 第 11 週 | Unit 8: Ownership and Smart Pointers |
| 第 12 週 | Unit 9: Modern C++ (assignment #5) |
| 第 13 週 | Unit 10: C++ and C for Python |
| 第 14 週 | Unit 11: Array Code in C++ (assignment #6) |
| 第 15 週 | Unit 12: Advanced Python |
| 第 16 週 | Project presentation 1 |
| 第 17 週 | No meeting (new year) |
| 第 18 週 | Project presentation 2 or TBD |
Textbook: None References: * Computer Systems: A Programmer's Perspective: https://csapp.cs.cmu.edu/ * Python documentation: https://docs.python.org/3/ * Cppreference: https://en.cppreference.com/ * Effective Modern C++, Scott Meyer, O'Reilly, 2014 * modmesh (example system of this course) source code: https://github.com/solvcon/modmesh * pybind11 source code: https://github.com/pybind/pybind11 * cpython source code: https://github.com/python/cpython * numpy source code: https://github.com/numpy/numpy
- 地點
- By appointment
- 時間
- N/A
- 聯絡方式
- Send email to yyc at solvcon.net, with "[nsd-course]" prefix in the subject line.