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.
Explores optimization strategies for deep learning accelerators, emphasizing data movement reduction through batching, dataflow optimizations, and compression.
Explores the landscape of big data, memory importance in online services, challenges faced by memory systems, emerging DRAM technologies, and storage-class memory.
Explores challenges in new data centers, large internet service growth, power consumption, availability, storage management, software layers, and energy efficiency.
Covers the basics of parallel programming, including concurrency, forms of parallelism, synchronization, and programming models like PThreads and OpenMP.