Explores multithreading in computer architecture, focusing on pipeline utilization and performance impact in various techniques, including blocked and fine-grained multithreading.
Discusses scheduling internals, metrics, and policies in computer systems, emphasizing efficiency and the complexities of modern multi-core architectures.
Explores parallelism in programming, emphasizing trade-offs between programmability and performance, and introduces shared memory parallel programming using OpenMP.
Explores GPUs' architecture, CUDA programming, image processing, and their significance in modern computing, emphasizing early start and correctness in GPU programming.
Covers semester projects, project logistics, successful project examples, proposal writing, and various project options related to systems, threading, serverless programming, virtual memory, cloud benchmarking, and AI accelerators.
