Covers the basics of parallel programming, including concurrency, forms of parallelism, synchronization, and programming models like PThreads and OpenMP.
Explores scalable synchronization mechanisms for many-core operating systems, focusing on the challenges of handling data growth and regressions in OS.
Explores parallelism in programming, emphasizing trade-offs between programmability and performance, and introduces shared memory parallel programming using OpenMP.
Explores the concept of locking for mutual exclusion in OS, covering race conditions, parallelism, atomic instructions, deadlock prevention, and best practices.
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 operating system's role as a referee in managing resources and ensuring security through fault isolation, resource sharing, and communication.
