<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[xxt228的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/xxt228</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; xxt228]]></copyright><item><title><![CDATA[Git常用命令总结]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/133465137</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/133465137</guid><author>xxt228</author><pubDate>Sun, 01 Oct 2023 15:12:59 +0800</pubDate><description><![CDATA[向远端仓库提交代码时，需要在远端仓库添加本地生成的 ssh key。]]></description><category></category></item><item><title><![CDATA[CUDA矩阵乘法]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/132053426</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/132053426</guid><author>xxt228</author><pubDate>Wed, 02 Aug 2023 00:46:07 +0800</pubDate><description><![CDATA[【代码】CUDA矩阵乘法。]]></description><category></category></item><item><title><![CDATA[CUDA矩阵转置]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/132053098</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/132053098</guid><author>xxt228</author><pubDate>Tue, 01 Aug 2023 23:55:36 +0800</pubDate><description><![CDATA[【代码】CUDA矩阵转置。]]></description><category></category></item><item><title><![CDATA[CUDA数组求和&求最大值]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/132051476</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/132051476</guid><author>xxt228</author><pubDate>Tue, 01 Aug 2023 21:50:59 +0800</pubDate><description><![CDATA[【代码】CUDA数组求和&求最大值。]]></description><category></category></item><item><title><![CDATA[CUDA的内存组织]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/132001604</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/132001604</guid><author>xxt228</author><pubDate>Mon, 31 Jul 2023 18:13:20 +0800</pubDate><description><![CDATA[目前市面上的教材普遍翻译得都有点问题，且经常会互相矛盾因此主要内容参考官方的。]]></description><category></category></item><item><title><![CDATA[Fermi架构GPU个人笔记]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/131882716</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/131882716</guid><author>xxt228</author><pubDate>Mon, 24 Jul 2023 01:48:03 +0800</pubDate><description><![CDATA[在Cuda Core前，还有一种的概念，其实就是Cuda Core，从Fermi架构开始，SP就改叫Cuda Core了在后续新退出的架构中，还会有不同类型的Core并放在同一个SM中，像从Volta架构开始，就变成了INT32、FP32、Tensor Core，更好地支持并发执行。Cuda Core的概念也慢慢淡化，取而代之的是更加细致的Core种类划分如果在Warp中没有32个Thread需要工作，那么Warp虽然还是作为一个整体运行,但这部分Thread是处于非激活状态的。]]></description><category></category></item><item><title><![CDATA[Eigen3使用cmake配置的一个小坑]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/131446589</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/131446589</guid><author>xxt228</author><pubDate>Wed, 28 Jun 2023 23:18:51 +0800</pubDate><description><![CDATA[usr/share/eigen3/cmake/Eigen3Config.cmake是find_package()查找Eigen3库的依据，进入文件中可以看到如下，是没有库的信息的。当然，如果你不愿意用find_package()搜索的方法，也可以直接。然后在CMakeLists.txt中补充以下即可把头文件制定出来。CMakeLists中如果这么写。]]></description><category></category></item><item><title><![CDATA[nn.Conv1d(in_channels=c_in, out_channels=d_model, kernel_size=3)的维度转换理解]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/131088816</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/131088816</guid><author>xxt228</author><pubDate>Wed, 07 Jun 2023 15:44:20 +0800</pubDate><description><![CDATA[本人在项目中经常碰到利用nn.Conv1d实现的全连接层进行维度转化，下面以实现维度由7到512的转变为例子，介绍维度转化的过程。]]></description><category></category></item><item><title><![CDATA[C++项目更改位置或重命名后无法编译与运行]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/129768209</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/129768209</guid><author>xxt228</author><pubDate>Sat, 25 Mar 2023 16:07:31 +0800</pubDate><description><![CDATA[这个错误提示是由于 CMakeCache.txt 目录与创建 CMakeCache.txt 的目录不同导致的。这可能会导致二进制文件被创建在错误的位置。只要删除build，然后重新编译就行了。]]></description><category></category></item><item><title><![CDATA[pd.loc[]中切片的一个小辨析]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/129305835</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/129305835</guid><author>xxt228</author><pubDate>Thu, 02 Mar 2023 17:50:06 +0800</pubDate><description><![CDATA[pd.loc[]的一个小坑]]></description><category></category></item><item><title><![CDATA[机械革命蛟龙16ubuntu双系统的移除与重装]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/129067594</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/129067594</guid><author>xxt228</author><pubDate>Sat, 25 Feb 2023 19:55:49 +0800</pubDate><description><![CDATA[ubuntu22.04重装流程]]></description><category></category></item><item><title><![CDATA[机械革命蛟龙16Windows重装流程]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/129167955</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/129167955</guid><author>xxt228</author><pubDate>Thu, 23 Feb 2023 22:38:42 +0800</pubDate><description><![CDATA[系统重装流程分享，如果搞深度学习的也可以参考参考环境搭建那部分的流程]]></description><category></category></item><item><title><![CDATA[opencv安装后cv::imshow无法运行]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/128874259</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/128874259</guid><author>xxt228</author><pubDate>Fri, 03 Feb 2023 19:05:21 +0800</pubDate><description><![CDATA[opencv安装后cv::imshow无法运行]]></description><category></category></item><item><title><![CDATA[tensorboard显示数据不全]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/128833999</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/128833999</guid><author>xxt228</author><pubDate>Wed, 01 Feb 2023 15:01:40 +0800</pubDate><description><![CDATA[显示结果的采样是有间隔的、结果显示不全的解决方案]]></description><category></category></item><item><title><![CDATA[学习笔记：基于Transformer的时间序列预测模型]]></title><link>https://blog.youkuaiyun.com/xxt228/article/details/128754364</link><guid>https://blog.youkuaiyun.com/xxt228/article/details/128754364</guid><author>xxt228</author><pubDate>Mon, 23 Jan 2023 23:53:58 +0800</pubDate><description><![CDATA[基于Transformer的时间序列预测]]></description><category></category></item></channel></rss>