DTE-3607 Systems Programming for Computational Engineering - 10 stp

Efficient implementation and practical aspects of scientific instrumentation.

Fundamental tools of C++ to enforce type safe programming of systems software:

• Concepts, templates, encapsulation (structs/classes and namespaces),
• abstraction, inheritance, type elision,
• memory-management and owners,
• advanced use of polymorphism, and strict static analysis.

Instrumentation using static and dynamic analysis:

• Branch misprediction,
• cache-misses,
• reliable and statistically relevant benchmarking, and
• debugging.

Systems programming demonstrated using computational engineering applications

• correct-tool-for-the-job by choosing the best approach to solve a given problem,
• hands-on experience with data-driven approaches and how they differ from object-oriented approaches,
• modularization and distribution of work,
• efficient linear-algebra libraries,
• utilization of differential geometry and vector mechanics,
• numerical accuracy and reliable metrics

A relevant undergraduate bachelor Engineering programme with minimum 25 credits mathematic, 5 credits statistics and 7,5 credits Physics

Application Code: 9371

Prerequisite(s) Knowledge of and experience with C++ and object oriented analysis, design and programming.

Knowledge:

• A type-safe programming subset of C++ and its related core guidelines.
• Software profiling via dynamic program analysis that measures time- and space complexity of a program and methods used to determine best-approaches based on domain specific problems and target architecture.
• Domain specific knowledge in geometry and related mathematical spaces, simulation and ODE-solvers.
• Knows how to use and write program libraries and APIs, and understands how this relates to end-user applications.

Skills:

• Can work independently with software development, by analyzing sub-problems and make plans for solving them analytically.
• Can construct large and complex computer programs for execution on multiple computer architectures.
• Can choose the right implementation approach based on scientifically founded reasoning, metrics, instrumentation, and analysis.

General competence:

• Utilize computers to solve problems in engineering applicable to a variety of industries and academic fields.
• The candidate is influenced to maintain and develop curiosity and values such as openness, precision, and the importance of distinguishing between knowledge and opinions.
• Present results in a scientific report, which clearly presents the candidate's own contribution within the problem context.