Superscalars: Execution and Cache Requirements

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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.