Advanced Parallel Processing
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 UpdatesAdvanced Parallel Processing Syllabus — Unit-wise Content
The official GTU curriculum for Advanced Parallel Processing (subject code 3725503) as prescribed for CE(P · Semester 2 divides the course into 6 units, covering 32 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 (3725503)Unit 1 Parallel Processing Concepts
- Physical Organization of Parallel Platform
- Threads and Processes
- Multi-processing OS, Data and flow dependence
- Race conditions
- Synchronization and communication fundamentals
- concurrency control
- General concepts
Unit 2 Processors and Multi-Core Architectures
- Processors types CISC
- pipelining etc.
- Software and hardware multithreading – SMT and CMP architectures – Design issues – Case studies – Intel Multi- core architecture – SUN CMP architecture – IBM cell architecture
- Data- Parallel and Data-Flow Systems Connection MachineCM5
- Vector processing
- In-order execution
- Instruction-Level Parallelism etc., FMA, 32 and 64 bit types, ISA
Unit 3 Memory and Cache
- Distributed and shared memory architectures
- Types of Cache
- Cache Line and False Sharing
- Cache coherency
- Optimizations of Cache Performance
Unit 4 Performance Metrics and scalability analysis
- Basic Principles - Sources of inefficiency Metrics: Execution time
- Throughput vs
- Performance analysis
Unit 5 Programming Models, Parallel Algorithms Design
- Decomposition Techniques: Data parallelism
- Functional parallelism
- Divide and Conquer etc.
- Characteristics of Tasks and Interactions
- Mapping Techniques for Load Balancing
- Methods for Containing Interaction Overheads
- Granularity of parallelism
- Case Studies
Unit 6 Optimizations
- Importance of Code optimization
- Compiler optimization
Study on Android App:
