數值軟體開發

Numerical Software Development

學期

112-1

學分

3 學分

當期課號

535702

永久課號

CSDS30003

開課單位

數據科學與工程研究所碩士班

授課教師

陳永昱

校區

光復

類別

選修

上課時間表

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

概述

The full syllabus is at https://yyc.solvcon.net/en/latest/nsd/schedule/23au_nycu/schedule23au.html . Please read it carefully before taking the course. 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.

先修科目

Critical discussion is required for the practical course and the project development. If you don't feel comfortable expressing yourself, think twice before taking the course. 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.

教學方式

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.

評分方式

* 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.

課程大綱

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

週次計畫

週次	主題
第 1 週	Introduction
第 2 週	Unit 1: Fundamental Engineering (assignment #1)
第 3 週	Unit 2: Python and Numpy (proposal open)
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	Mid-term examination (proposal due)
第 9 週	Unit 6: SIMD (Vector Processing)
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
第 17 週	No meeting (new year)
第 18 週	To be planned

教科書

Course notes: https://yyc.solvcon.net/en/latest/nsd/ 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

Office Hours

地點: By appointment
時間: N/A
聯絡方式: Send email to yyc at sciwork.dev, with "[nsd-course]" prefix in the subject line.