Covers the principles of synchronization in parallel computing, focusing on shared memory synchronization and different methods like locks and barriers.
Covers the basics of parallel programming, including concurrency, forms of parallelism, synchronization, and programming models like PThreads and OpenMP.
Explores the significance of lock-free synchronization for achieving low latency in distributed systems and discusses practical solutions for unique identifier generation and messaging queues.
Explores GPUs' architecture, CUDA programming, image processing, and their significance in modern computing, emphasizing early start and correctness in GPU programming.
Explores lock-free synchronization for performance and scalability in distributed systems, covering unique identifier generation, messaging queues, and atomic RDMA reads.
Explores parallelism in programming, emphasizing trade-offs between programmability and performance, and introduces shared memory parallel programming using OpenMP.
