Modern computing systems rely on parallel execution to maximize performance and efficiency. This course introduces parallel programming concepts in Java, helping learners understand how to design and implement multi-threaded programs that leverage multi-core processors and distributed computing environments.
Participants will start by exploring Java’s concurrency model, learning how to manage threads, synchronization, and shared resources. The course then introduces task parallelism, covering techniques such as work-stealing, Fork/Join framework, and parallel streams. Additionally, learners will gain practical experience with thread pools, performance tuning, and avoiding common pitfalls such as deadlocks and race conditions.
By the end of the course, learners will be able to write efficient, parallelized Java applications, enabling them to build high-performance systems for scientific computing, data processing, and large-scale enterprise applications.
Sections Included:
- Introduction to Parallel Computing – Understanding the need for parallelism in modern applications.
- Concurrency and Multi-Threading in Java – Managing threads, synchronization, and shared resources.
- Task Parallelism and Thread Pools – Implementing parallel tasks using Java’s Executor framework.
- Fork/Join Framework and Work-Stealing – Optimizing performance with divide-and-conquer strategies.
- Parallel Streams and Functional Programming – Leveraging Java Streams API for efficient data processing.
- Performance Optimization and Debugging – Avoiding deadlocks, race conditions, and tuning applications for scalability.
- Building High-Performance Java Applications – Applying parallel programming techniques to real-world scenarios.
Benefits Upon Completion:
- Gain proficiency in parallel programming techniques using Java.
- Learn to manage concurrency, synchronization, and thread safety.
- Implement task parallelism and work-stealing algorithms for efficiency.
- Optimize Java applications for scalability and high-performance computing.
- Build real-world projects leveraging multi-threading and parallel execution.
