<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:media="http://search.yahoo.com/mrss/"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>gpu - 四号程序员</title>
	<atom:link href="https://www.coder4.com/archives/tag/gpu/feed" rel="self" type="application/rss+xml" />
	<link>https://www.coder4.com</link>
	<description>Keep It Simple and Stupid</description>
	<lastBuildDate>Tue, 27 May 2025 07:36:52 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=6.8.3</generator>
	<item>
		<title>Rockchip的RK3588的CPU上测试Electron(以及硬件加速)</title>
		<link>https://www.coder4.com/archives/8426</link>
					<comments>https://www.coder4.com/archives/8426#comments</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Tue, 29 Apr 2025 10:33:12 +0000</pubDate>
				<category><![CDATA[Linux]]></category>
		<category><![CDATA[cpu]]></category>
		<category><![CDATA[electron]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[RK3588]]></category>
		<category><![CDATA[硬件加速]]></category>
		<guid isPermaLink="false">https://www.coder4.com/?p=8426</guid>

					<description><![CDATA[1 安装Node.js # Download and install nvm: curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.3/install.sh &#124; bash # in lieu of restarting the shell \. "$HOME/.nvm/nvm.sh" # Download and install Node.js: nvm install 20 # Verify t[......] 继续阅读]]></description>
		
					<wfw:commentRss>https://www.coder4.com/archives/8426/feed</wfw:commentRss>
			<slash:comments>1</slash:comments>
		
		
			</item>
		<item>
		<title>开发板GPU跑分记录</title>
		<link>https://www.coder4.com/archives/8424</link>
					<comments>https://www.coder4.com/archives/8424#respond</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Mon, 28 Apr 2025 10:33:58 +0000</pubDate>
				<category><![CDATA[Linux]]></category>
		<category><![CDATA[glmark2]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[驱动]]></category>
		<guid isPermaLink="false">https://www.coder4.com/?p=8424</guid>

					<description><![CDATA[跑分附录 我的香橙派5 pro (xfce) OpenGL Information GL_VENDOR: Mesa/X.org GL_RENDERER: llvmpipe (LLVM 15.0.6, 128 bits) GL_VERSION: 4.5 (Compatibility Profile) Mesa 22.3.6 Surface Config: buf=32 r=8 g=8 b=8 a=8 depth=32 stencil=0 samples=0 S[......] 继续阅读]]></description>
		
					<wfw:commentRss>https://www.coder4.com/archives/8424/feed</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>CUDA GPU英伟达官方打分</title>
		<link>https://www.coder4.com/archives/7861</link>
					<comments>https://www.coder4.com/archives/7861#respond</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Tue, 09 May 2023 11:46:48 +0000</pubDate>
				<category><![CDATA[计算机技术]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[打分]]></category>
		<guid isPermaLink="false">https://www.coder4.com/?p=7861</guid>

					<description><![CDATA[https://developer.nvidia.com/cuda-gpus GPU的性能对比，可以直接看这个表[......] 继续阅读]]></description>
		
					<wfw:commentRss>https://www.coder4.com/archives/7861/feed</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>阿里云的gpu实例配置paddlepaddle</title>
		<link>https://www.coder4.com/archives/7050</link>
					<comments>https://www.coder4.com/archives/7050#respond</comments>
		
		<dc:creator><![CDATA[coder4]]></dc:creator>
		<pubDate>Thu, 23 Jul 2020 11:21:15 +0000</pubDate>
				<category><![CDATA[机器学习]]></category>
		<category><![CDATA[cuda]]></category>
		<category><![CDATA[gpu]]></category>
		<category><![CDATA[paddle]]></category>
		<guid isPermaLink="false">https://www.coder4.com/?p=7050</guid>

					<description><![CDATA[1 gpu实例 CentOS 7.6 选择自动安装cuda，勾选自动 CUDA 版本 10.1.168 / Driver 版本 440.64.00 / CUDNN 版本 7.6.5 2 切换源 curl -o /etc/yum.repos.d/CentOS-Base.repo http://mirrors.aliyun.com/repo/Centos-7.repo yum clean all yum makecache 3 安装Python、paddle yum i[......] 继续阅读]]></description>
		
					<wfw:commentRss>https://www.coder4.com/archives/7050/feed</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
	</channel>
</rss>
