Instruction-level parallelism

Applied sciences
Computer engineering
Hardware engineering
Microprocessors

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Related lectures (30)

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

VLIW Architectures: Compilers and Instruction Level Parallelism

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

Prediction and Speculation in Processor Design

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

Superscalars: Execution and Cache Optimization

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

Dynamic Scheduling

Explores dynamic scheduling in processor design to increase parallelism by executing instructions out of order, improving performance and efficiency.

Dynamic Scheduling in Processors: Enhancing Instruction Execution

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

Memory Consistency Models: Performance Impact and Parallel Computing

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

Superscalars: Execution and Cache Requirements

Explores superscalar processors and cache optimization for improved 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: Extending Pipelining for Parallelism

Delves into dynamic scheduling to enhance pipelining and enable out-of-order execution for improved performance.

Performance: Hardware and Software Optimization

Explores hardware and software optimization for system performance, emphasizing the importance of reducing delay per gate and improving architecture.

Concurrency and Parallelism: Visibility

Explores visibility in concurrency, memory models, shared memory, and hardware optimizations.

Expertise and Hands-On Teaching

Explores expertise, differences between experts and novices, and effective teaching strategies in hands-on settings.

Introduction to C++ Programming

Covers the basics of C++ programming, including writing a 'Hello world' program and understanding the compilation process.

Verifying Security Across Hardware & Software

Covers the verification of security across hardware and software, including verified algorithms and techniques for eliminating speculative leaks.

Atomic Operations: Basics and Applications

Covers the basics of atomic operations in concurrency and parallelism, including hardware-provided operations and synchronized algorithms.

Compilers: Challenges with Digital Signal Processors

Covers the challenges of compiling for digital signal processors due to their unique architectural features and irregularities.

Optimizing Library Interactions: Functionality and Modularity

Explores optimizing library interactions, functionality challenges, and modularity in modern workloads, emphasizing strong boundaries between systems and instruction-level optimizations.

GPUs: Introduction to CUDA

Introduces the basics of GPUs, CUDA programming, and thread synchronization for parallel computing applications.

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.

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