PX913-15 Introduction to Scientific Software Development
Introductory description
N/A.
Module aims
To equip students with a solid knowledge of the tools and techniques used in modern scientific software development and the associated tools used to work with the data produced.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Real computers (1 Lecture + 1 x 2hr workshop) - Describe the parts of a computer (memory, CPU disk etc). Introduction to representation of numbers in a computer. High and low-level languages, their purposes and suitability. Intro to the Linux command line, compiling existing code, compiling vs linking, common command line flags to compilers.
Version control (1 Lecture + 1 x 2hr workshops) - Practical use of git for version control, in particular add, commit, log, push and pull. Collaborative working using git: merging and conflicts.
Programming in C or Fortran (4 lectures + 4 x 2hr workshops) - Boilerplate and support code. Recap of loops, conditionals and functions. Arrays and pointers (in C). Arrays and array intrinsics (in Fortran). Use of and linking of library code.
Codes in the real world (1 lecture + 1 x 2hr workshop) - Output files, code control, testing and verification principles.
Debugging and profiling (1 lecture + 1 x 2hr workshop) - Use of standard debugging tools, approaches to finding bugs. Brief introduction to profiling and optimisation strategies.
Introduction to miniproject (1 lecture) - Description of the projects, how to work with others in software development, expectations and requirements.
Consolidation (1 x 2hr workshop) - When starting with the miniproject one final workshop to help people with any questions they have about any of the tools or techniques that they will need.
Python data visualisation (1 lecture + 1 x 2hr workshop) - Introduction to python for loading data from file and plotting data in Matplotlib, and Mayavi or similar.
Learning outcomes
By the end of the module, students should be able to:
- Understand the basic internals of a computer.
- Be able to use version control for reproducible research.
- Be able to write numerical codes in Fortran or C.
- Understand the common parts of computer code (loops, conditionals, pointers, arrays etc.).
- Be able to compile code and manage libraries.
- Be able to understand the operation of, and make simple modifications to Fortran or C code.
- Acquire basic experience with symbolic debuggers.
- To work alone and in small groups to produce a piece of working code using best principles.
- To have used common tools for data analysis and visualization in Python.
Indicative reading list
Introduction to programming with Fortran : with coverage of Fortran 90, 95, 2003, 2008 and 77, Ian D. Chivers, Jane Sleightholme
The C programming language Kernighan, Brian W.; Ritchie, Dennis M
Introducing Unix and Linux, Joy, Mike; Jarvis, Stephen; Luck, Michael
https://www.cprogramming.com/ website
Python data visualization cookbook, Igor Milovanović
Subject specific skills
To equip students with a solid knowledge of the tools and techniques used in modern scientific software development and the associated tools used to work with the data produced
understand the basic internals of a computer
be able to use version control for reproducible research
be able to write numerical codes in Fortran or C
understand the common parts of computer code (loops, conditionals, pointers, arrays etc.)
be able to compile code and manage libraries
be able to understand the operation of, and make simple modifications to Fortran or C code
acquire basic experience with symbolic debuggers
to work alone and in small groups to produce a piece of working code using best principles
to have used common tools for data analysis and visualization in Python
Transferable skills
Coding, debugging, project management, data analysis
Study time
| Type | Required |
|---|---|
| Lectures | 10 sessions of 1 hour (7%) |
| Practical classes | 10 sessions of 2 hours (13%) |
| Private study | 68 hours (45%) |
| Assessment | 52 hours (35%) |
| Total | 150 hours |
Private study description
Coding practice, further reading.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group A1
| Weighting | Study time | |
|---|---|---|
| Moodle Quizzes | 30% | 16 hours |
|
Conceptual understanding of computer architecture and underlying data representation. Tests understanding of the concepts of memory hierarchy and numerical precision. Practical understanding of the “git” version control system. Ability to interpret syntax of either Fortran2003 or ANSI C (C89). Critical evaluation of approaches to writing output files and visualising data. They should demonstrate independent judgement in selecting in-code data reduction versus output size and the practical consequences of these choices. |
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| Individual Programming Assignments | 45% | 16 hours |
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| Microproject | 25% | 20 hours |
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Students will work in pairs to generate a program in either C or Fortran solving a real but simple numerical problem. The program will be created under git version control and both students must have commits to the repository at the end of the project. The program will take input from a user, iterate through an algorithm and write one or more output files. The algorithm would once again be described in detail but implementation would be up to the students. Example problems would be the Ising model for spins (with details given to the students for dealing with random numbers), or solving the heat equation using Jacobi or Gauss-Seidel iteration. The project would be expected to be accompanied with a Python script to automake visualisation of output files. This would take the last 2 weeks of the course’s workshops and time over the subsequent holiday period. Submitted and marked at the start of the following term. Duration 5 Hours. |
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Feedback on assessment
Online quizzes will use instant feedback in Moodle/Quizbuilder or similar.\r\n\r\nProgramming assignments will be subject to individual electronic feedback. Earlier assignments will receive high marks if the submitted code is syntactically valid and capable of producing correct output. However, feedback will be provided on style, design and efficiency. Marks will be lost in later assignments if this feedback is not incorporated.\r\n\r\nFeedback on the microproject will be given via group meetings (one per project pair) with a member of the SCRTP research software engineering team.\r\n\r\n\r\n
Courses
This module is Core for:
- Year 1 of TPXA-F344 Postgraduate Taught Modelling of Heterogeneous Systems
- Year 1 of TPXA-F345 Postgraduate Taught Modelling of Heterogeneous Systems (PGDip)