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Covers the basics of parallel programming, including concurrency, forms of parallelism, synchronization, and programming models like PThreads and OpenMP.
Explores parallelism in programming, emphasizing trade-offs between programmability and performance, and introduces shared memory parallel programming using OpenMP.
Explores the significance of concurrency in enhancing system performance and responsiveness, emphasizing the need for synchronization and atomicity to prevent race conditions and non-determinism.
Covers the principles of synchronization in parallel computing, focusing on shared memory synchronization and different methods like locks and barriers.
Explores memory consistency, weak consistency, and language-level guarantees in memory ordering, emphasizing the importance of data race free programming.
