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NVIDIA CUDA Samples - Comprehensive Examples for Parallel Programming
Explore a wide range of samples demonstrating the features and capabilities of the NVIDIA CUDA Toolkit for accelerating parallel computing applications.
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Added on 2025年6月1日7,529
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LanguageProject Introduction
Summary
This repository provides a collection of source code examples designed to help developers learn and utilize the features of the NVIDIA CUDA platform. It covers various aspects of GPU programming, from basic kernel execution to advanced techniques.
Problem Solved
Learning parallel programming on GPUs, especially with a comprehensive platform like CUDA, can be challenging. These samples offer practical, runnable examples that illustrate specific concepts, making it easier for developers to understand and apply CUDA features effectively.
Core Features
Diverse Sample Categories
Samples are organized by topic (e.g., basic, utilities, libraries, scientific) covering various CUDA features and use cases.
Detailed Source Code
Each sample includes well-commented source code in C/C++, with some examples in Fortran and Python, illustrating key CUDA programming patterns.
Build and Run Infrastructure
Includes build scripts and instructions to easily compile and run samples on compatible systems with the CUDA Toolkit installed.
Tech Stack
CUDA Toolkit
C++
C
Fortran
Python
使用场景
These samples are invaluable for anyone working with or learning about GPU-accelerated parallel computing using the NVIDIA CUDA platform. Specific use cases include:
Scenario 1: Learning CUDA Fundamentals
Details
Beginner developers can start with basic samples to understand concepts like kernel launches, memory allocation (host and device), and data transfer.
User Value
Provides hands-on examples to build a foundational understanding of CUDA programming.
Scenario 2: Exploring Advanced CUDA Features
Details
Experienced users can dive into samples demonstrating advanced topics such as CUDA streams, multiple GPUs, shared memory optimizations, and library usage (cuFFT, cuBLAS, etc.).
User Value
Offers concrete examples to learn and apply complex CUDA features for performance tuning and specialized tasks.
Scenario 3: Benchmarking and Performance Analysis
Details
Utilize performance-oriented samples to understand how different kernel implementations and memory access patterns affect performance on specific hardware.
User Value
Aids in identifying performance bottlenecks and implementing optimization strategies in user applications.
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