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Lecture
GPUs: Multithreading and Architecture
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GPU Memory Hierarchy and Optimization
Explores GPU memory hierarchy, optimization challenges, and algorithm efficiency.
Data-Parallel Programming: Vector & SIMD Processors
Explores data-parallel programming with vector processors and SIMD, and introduces MapReduce, Pregel, and TensorFlow.
Advanced Multiprocessor Architecture
Covers Advanced Multiprocessor Architecture, discussing course logistics, components, grading, and trends in modern computing systems.
Dynamic Scheduling in Processors: Enhancing Instruction Execution
Covers dynamic scheduling in processors, focusing on out-of-order execution and managing instruction dependencies effectively.
GPU Memory Hierarchy: Optimization
Explores GPU memory hierarchy, CUDA processing flow, optimizations, and parallelism efficiency on GPUs.
GPU Memory Hierarchy: Optimization
Discusses GPU memory hierarchy and optimization strategies for efficient memory access and execution.
GPU Introduction: Performance and Programming
Explores the motivation and advantages of using GPUs for computation, focusing on their performance and programming through CUDA.
Architecture Essentials: Understanding Computer Systems
Provides an overview of computer architecture, focusing on the von Neumann architecture and its components, including the CPU and memory management units.
Cache Memory
Explores cache memory design, hits, misses, and eviction policies in computer systems, emphasizing spatial and temporal locality.
Accelerator-centric OS Architecture
By the instructor Mark Silberstein explores accelerator-centric OS architecture and the role of CPUs in modern computers.
