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parallel101 avatar

parallel101/course

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Course

This project is a technical curriculum and set of educational resources focused on parallel programming, high-performance computing, and systems programming. It provides a structured course covering the implementation of parallel algorithms and multithreading techniques for processing large datasets.

The project includes a systems programming guide for modern language features, a framework for lock-free concurrency patterns, and a manual for optimizing CPU and GPU performance through assembly analysis and cache management.

The material covers hardware performance tuning, the implementation of parallel algorithms such as reductions and matrix multiplication, and low-level architectural strategies including vectorization and manual memory management.

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Features

  • High-Performance Computing - Provides a comprehensive framework for executing computationally intensive tasks across parallel hardware architectures.
  • Parallel Programming - Offers primitives and patterns for implementing multi-threading and concurrent execution.
  • Parallel Programming Curricula - Provides a structured technical curriculum focusing on high-performance computing and parallel algorithm implementation.
  • CPU Instruction Optimizations - Improves execution speed through low-level optimizations targeting specific processor instruction sets.
  • Hardware-Level Performance Tuning - Employs SIMD and inline assembly to achieve maximum hardware execution speed.
  • Lock-Free Atomic Containers - Implements thread-safe data structures using atomic primitives to avoid mutex overhead.
  • Manual Memory Management - Teaches explicit control over memory allocation and deallocation for predictable system performance.
  • Parallel Algorithms - Implements fundamental data-parallel operations such as reductions, scans, and matrix multiplication.
  • Concurrent Programming Patterns - Provides architectural patterns for designing multi-threaded systems that ensure data consistency.
  • Cache-Aware Memory Access - Provides techniques for aligning data structures and access patterns to maximize CPU cache hits.
  • SIMD-Accelerated Arithmetic - Utilizes processor-specific vector instruction sets to accelerate mathematical operations like matrix multiplication.
  • Template Metaprogramming - Employs compile-time logic to generate specialized code for improved runtime efficiency and type safety.
  • CPU and GPU Performance Manuals - Provides a detailed manual for increasing speed via assembly analysis, cache optimization, and GPU memory management.
  • Systems Programming Proficiency - Guides learners toward mastering modern language features for the creation of efficient system code.
  • Concurrency Patterns - Ships a collection of implementations and examples for multi-threaded execution and parallel task processing.
  • Modern C++ Feature Adoption - Utilizes modern C++ additions like smart pointers and structured bindings to write efficient system code.
  • C++ Programming Mastery - Provides advanced guides on STL, object models, and modern C++ features for systems programming.
  • Multi-Core Parallelization - Demonstrates splitting large datasets into independent chunks for parallel execution across CPU cores.
  • Learning & Reference - Parallel programming and optimization course
4,166 stars·561 forks·C++·other·31 views

Star history

Star history chart for parallel101/courseStar history chart for parallel101/course

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Frequently asked questions

What does parallel101/course do?

This project is a technical curriculum and set of educational resources focused on parallel programming, high-performance computing, and systems programming. It provides a structured course covering the implementation of parallel algorithms and multithreading techniques for processing large datasets.

What are the main features of parallel101/course?

The main features of parallel101/course are: High-Performance Computing, Parallel Programming, Parallel Programming Curricula, CPU Instruction Optimizations, Hardware-Level Performance Tuning, Lock-Free Atomic Containers, Manual Memory Management, Parallel Algorithms.

Which projects share features with parallel101/course?

Projects with overlapping indexed features include: cpp-taskflow/cpp-taskflow — Cpp-taskflow is a C++ task-parallelism framework and task graph scheduler designed to manage and execute complex… c3lang/c3c — c3c is the compiler for the C3 programming language, transforming source code into executable binaries, static… federico-busato/modern-cpp-programming — This project is a comprehensive educational resource and programming course covering C++ language semantics and… ispc/ispc — ISPC is a vectorizing compiler and SIMD parallel programming language that implements a single program multiple data… open-mpi/ompi. anthonycalandra/modern-cpp-features — This project is a comprehensive collection of reference materials, including a language cheatsheet, a standard library…

Projects sharing features with Course

These projects share indexed features with Course. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • cpp-taskflow/cpp-taskflowcpp-taskflow avatar

    cpp-taskflow/cpp-taskflow

    12,014View on GitHub↗

    Cpp-taskflow is a C++ task-parallelism framework and task graph scheduler designed to manage and execute complex dependency graphs of parallel tasks across CPU and GPU hardware. It provides a parallel algorithm library for high-performance implementations of reductions, sorts, pipelines, and iterations. The framework distinguishes itself through its ability to offload heavy computational workloads from a task graph to graphics processors for acceleration. It also includes a task profiling tool and a performance analysis interface for visualizing task execution flow and dependency structures t

    C++
    View on GitHub↗12,014
  • c3lang/c3cc3lang avatar

    c3lang/c3c

    5,147View on GitHub↗

    c3c is the compiler for the C3 programming language, transforming source code into executable binaries, static libraries, or dynamic libraries using an LLVM backend. It implements a system based on result-based error handling, scoped memory pooling, and a semantic macro system. The compiler provides first-class support for hardware-backed SIMD vectors that map directly to processor instructions and enables runtime polymorphism through interface-based dynamic dispatch. The project covers a broad set of low-level capabilities, including manual and pooled memory management, inline assembly inte

    C3c3compilerlanguage
    View on GitHub↗5,147
  • federico-busato/modern-cpp-programmingfederico-busato avatar

    federico-busato/Modern-CPP-Programming

    15,808View on GitHub↗

    This project is a comprehensive educational resource and programming course covering C++ language semantics and features from C++03 through C++26. It provides structured tutorials and technical guides focused on modern C++ development. The material offers specialized instruction on template metaprogramming, including the use of type traits and compile-time computations. It features detailed guides on concurrency and parallelism for multi-core execution, as well as a reference for software design applying SOLID principles and RAII. Additionally, it covers build performance optimization to redu

    HTMLc-plus-pluscode-qualitycompilers
    View on GitHub↗15,808
  • ispc/ispcispc avatar

    ispc/ispc

    2,843View on GitHub↗

    ISPC is a vectorizing compiler and SIMD parallel programming language that implements a single program multiple data model. It serves as a toolchain for translating C-based code with parallel extensions into optimized machine code for various CPU and GPU architectures using an LLVM backend. The compiler is designed for cross-platform SIMD toolchain support, generating specialized instruction sets for x86 SSE/AVX, ARM NEON, and Intel GPU from a single source. It features a runtime dispatch mechanism that selects the most efficient hardware-specific implementation for the current system during

    C++compilerintelispc
    View on GitHub↗2,843
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