<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>CUDA on timerring</title><link>https://blogs.timerring.com/tags/cuda/</link><description>Recent content in CUDA on timerring</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 10 Aug 2023 11:59:16 +0800</lastBuildDate><atom:link href="https://blogs.timerring.com/tags/cuda/index.xml" rel="self" type="application/rss+xml"/><item><title>CUDA Matrix Multiplication and Transpose</title><link>https://blogs.timerring.com/posts/cuda-matrix-multiplication-and-transpose/</link><pubDate>Thu, 10 Aug 2023 11:59:16 +0800</pubDate><guid>https://blogs.timerring.com/posts/cuda-matrix-multiplication-and-transpose/</guid><description>&lt;p>通过代码实践 CUDA 矩阵乘法与转置，理解 GPU 存储单元与并行计算。&lt;/p></description></item><item><title>CUDA Thread Indexing</title><link>https://blogs.timerring.com/posts/cuda-thread-indexing/</link><pubDate>Wed, 09 Aug 2023 10:19:58 +0800</pubDate><guid>https://blogs.timerring.com/posts/cuda-thread-indexing/</guid><description>&lt;p>结合向量相加和图像处理，介绍 CPU 与 GPU 内存操作、线程索引以及 Grid 和 Block 的配置。&lt;/p>
&lt;p>我们要处理的问题&lt;/p>
&lt;p>&lt;img src="https://raw.githubusercontent.com/timerring/scratchpad2023/main/2023/20230809101958.png" alt="" />&lt;/p>
&lt;p>如图，有离散型的，例如向量相加等等。有 local 卷积类型的，用其他一片的元素值求得一个元素。还有 All to All 类型的，类似于傅里叶变换。&lt;/p>
&lt;p>回顾一下 CUDA 程序的编写：
&lt;img src="https://raw.githubusercontent.com/timerring/scratchpad2023/main/2023/20230809104417.png" alt="" />&lt;/p>
&lt;ol>
&lt;li>把输入数据从 CPU 内存复制到 GPU 显存&lt;/li>
&lt;li>在执行芯片上缓存数据，加载 GPU 程序并执行&lt;/li>
&lt;li>将计算结果从 GPU 显存中复制到 CPU 内存中&lt;/li>
&lt;/ol></description></item><item><title>Writing Your First CUDA Program</title><link>https://blogs.timerring.com/posts/cuda-first-program/</link><pubDate>Wed, 02 Aug 2023 11:53:41 +0800</pubDate><guid>https://blogs.timerring.com/posts/cuda-first-program/</guid><description>&lt;p>从第一个 CUDA 程序开始，实践 NVCC 编译、Makefile、多文件编译、线程索引和性能分析。&lt;/p></description></item><item><title>CUDA Programming Model</title><link>https://blogs.timerring.com/posts/cuda-programming-model/</link><pubDate>Fri, 28 Jul 2023 20:27:45 +0800</pubDate><guid>https://blogs.timerring.com/posts/cuda-programming-model/</guid><description>&lt;p>梳理 CUDA 异构计算、执行空间说明符、线程层次、NVCC 编译流程和 NVProf 性能分析。&lt;/p></description></item><item><title>GPU Hardware Architecture</title><link>https://blogs.timerring.com/posts/gpu-hardware-architecture/</link><pubDate>Fri, 28 Jul 2023 18:13:08 +0800</pubDate><guid>https://blogs.timerring.com/posts/gpu-hardware-architecture/</guid><description>&lt;p>介绍 CPU 与 GPU 的架构差异、GPU 硬件平台、Jetson 设备及 Amdahl 定律。&lt;/p></description></item><item><title>Introduction to CUDA and Linux Basics</title><link>https://blogs.timerring.com/posts/cuda-introduction-and-linux-basics/</link><pubDate>Mon, 24 Jul 2023 21:09:38 +0800</pubDate><guid>https://blogs.timerring.com/posts/cuda-introduction-and-linux-basics/</guid><description>&lt;p>从 CUDA 与 NVIDIA 技术生态入门，介绍 Ubuntu、Jetson 开发环境、权限管理、SSH 和 Makefile。&lt;/p></description></item><item><title>Introduction to CUDA</title><link>https://blogs.timerring.com/posts/introduction-to-cuda/</link><pubDate>Fri, 08 Jul 2022 11:58:01 +0800</pubDate><guid>https://blogs.timerring.com/posts/introduction-to-cuda/</guid><description>&lt;p>介绍 CUDA 的基本概念、支持的编程语言、发展历程及 GPU 加速计算的应用。&lt;/p></description></item></channel></rss>