High Performance Computing Solution & Applications
Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.
English Book & Chapters
English Book Coming Soon
We are working hard to add this material. Stay tuned for updates!
Follow on Instagram for UpdatesGTU Previous Year Papers
Papers Coming Soon
We are working hard to add this material. Stay tuned for updates!
Follow on Instagram for UpdatesHigh Performance Computing Solution & Applications Syllabus — Unit-wise Content
The official GTU curriculum for High Performance Computing Solution & Applications (subject code 3725502) as prescribed for CE(P · Semester 2 divides the course into 4 units, covering 26 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3725502)Unit 1 Application porting, execution and scalability analysis
- Compiler flags
- memory alignment of data
- porting of application on Linux Measurement of Application execution time and memory consumption with small
- medium and large datasets
- Scalability analysis and identification of performance bottlenecks
- Profiling of applications to find opportunities for performance optimization
- Addition of directives
- Restructuring of code for performance optimization
- Communication optimization through configuration of MPI calls of the underlying MPI implementation
- Partitioning applications for heterogeneous resources
- Use of existing libraries
- tools, and frameworks
Unit 2 Bioinformatics and Molecular Dynamics
- Basics of bio-informatics and Molecular Dynamics
- Sequence Search: e.g
- Sequence Alignment: e.g
- Sequence Assembly: e.g
- Molecular Dynamics: e.g
- Scientific data visualization and analytics: Integration of simulation
- data visualization and analytics on HPC
Unit 3 HPC Performance Measurement
- Computational Complexity Performance Measures of Parallel Algorithms: Power-Aware Computing and Communication Power-aware Processing Techniques
- Power-aware Memory Design
- Power-aware Interconnect Design
- Software Power Management
- Granularity and Partitioning
- Locality: temporal/spatial/stream/kernel
Unit 4 Case Studies (Scientific & Engineering Domains)
- Study and optimization of computational performance of applications Climatology: Basics of computational atmospheric and ocean sciences
Study on Android App:
