數值軟體開發(英文授課)

Numerical Software Development

學期

109-1

學分

3 學分

當期課號

5285

永久課號

IDS5008

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(英文授課) EC115 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

This course discusses the art to build numerical software, i.e., computer programs applying numerical methods for solving mathematical or physical problems. We will be using the combination of Python and C++ and related 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. Cherk course notes for details: https://github.com/yungyuc/nsd/tree/master/notebook/20au_nctu .

先修科目

This is a graduate or senior level course open to students who have taken computer architecture, 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. AWS Machine Image (AMI) and AWS educate will be used.

評分方式

* You are expected to learn programming languages yourself. Python is never a problem, but you could find it challenging to self-teach C++. 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 14 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 practices
Python and numpy
C++ and computer architecture
Matrix operations
Cache optimization
SIMD (vector processing)
Memory management
Smart pointers
Modern C++
C++ and C for Python
Array code in C++
Array-oriented design
Advanced Python

週次計畫

週次	主題
第 1 週	Lecture 1: Introduction
第 2 週	Lecture 2: Fundamental engineering practices (homework #1)
第 3 週	Lecture 3: Python and numpy (term project proposal start)
第 4 週	Lecture 4: C++ and computer architecture (homework #2)
第 5 週	Lecture 5: Matrix operations
第 6 週	Lecture 6: Cache optimization (homework #3)
第 7 週	Lecture 7: SIMD (term project proposal due)
第 8 週	Mid-term examination
第 9 週	Lecture 8: Memory management (homework #4)
第 10 週	Lecture 9: Smart pointers
第 11 週	Lecture 10: Modern C++ (homework #5)
第 12 週	Lecture 11: C++ and C for Python
第 13 週	Lecture 12: Array code in C++ (homework #6)
第 14 週	Lecture 13: Array-oriented design
第 15 週	Lecture 14: Advanced Python
第 16 週	Term project presentation
第 17 週	No meeting (optional lecture is not planned)
第 18 週	No meeting (optional lecture is not planned)

教科書

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 * Source code: cpython, numpy, xtensor, and pybind11

Office Hours

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