Lectures related to Superscalars: Execution and Cache Requirements

Superscalars: Execution and Cache Optimization

Explores superscalar processors, dynamic branch prediction, nonblocking caches, and control speculation.

VLIW Architectures: Compilers and Instruction Level Parallelism

Covers VLIW architectures and compilers, focusing on instruction level parallelism and optimization techniques.

Understanding Simultaneous Multithreading in Modern Processors

Covers simultaneous multithreading, its implementation, and its impact on processor performance.

Pipelining: Enhancing Computer Architecture Performance

Covers pipelining in computer architecture, focusing on its role in enhancing performance through instruction-level parallelism and addressing associated challenges.

Dynamic Scheduling in Processors: Enhancing Instruction Execution

Covers dynamic scheduling in processors, focusing on out-of-order execution and managing instruction dependencies effectively.

VLIW: Dynamically Scheduled Processors

Explores VLIW processors, focusing on scheduling complexity, ILP limitations, and code bloating.

Multi-threaded Processors

Covers the basics of multi-threaded processors, including design, performance impact, and pipeline utilization.

Prediction and Speculation in Processor Design

Covers prediction and speculation techniques in processor design to enhance performance and reduce execution delays.

Parallelism: Programming and Performance

Explores parallelism in programming, emphasizing trade-offs between programmability and performance, and introduces shared memory parallel programming using OpenMP.

Multithreading Basics: Design, Performance, and Impact

Covers the basics of multithreading, including design, performance impact, and GPU utilization.

Memory Consistency Models: Performance Impact and Parallel Computing

Covers memory consistency models, parallel computing, atomic subroutines, GPU architecture, and multithreading.

Instruction Set Extensions: High-Level Synthesis Techniques

Covers instruction set extensions and high-level synthesis techniques for optimizing embedded processors.

GPUs: Multithreading and Architecture

Explores GPUs' architecture, multithreading, and their role in machine learning, discussing limitations and future trends.

Data-Parallel Programming: Vector & SIMD Processors

Explores data-parallel programming with vector processors and SIMD, and introduces MapReduce, Pregel, and TensorFlow.

Implementation with Transistors

Covers the implementation of a processor with transistors and focuses on improving performance through various technologies and circuit designs.

GPUs: Architecture and Programming

Explores GPU architecture, multithreading, SIMD processors, and CUDA programming for parallel computing.

Multithreading: Pipeline Utilization and Performance Impact

Explores multithreading in computer architecture, focusing on pipeline utilization and performance impact in various techniques, including blocked and fine-grained multithreading.

Multi-Cycle MIPS Processor

Explores the design and performance analysis of a Multi-Cycle MIPS Processor compared to a Single-Cycle Processor, emphasizing benefits and downsides.

Computer Architecture: Circuits and Processors

Introduces computer architecture, covering logic circuits, adders, processors, and performance optimization.

Principles of Parallelism

Covers the basics of parallelism, including physical examples, historical context, multicore era, and parallel collections in Scala.