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cloudwin
04-28
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国际知名半导体研究机构SemiAnalysis称：华为云CloudMatrix 384领先英伟达和AMD的产品一代
cloudwin
2023-12-21
$NVIDIA Corp(NVDA)$
cloudwin
2023-12-06
$Advanced Micro Devices(AMD)$
cloudwin
2023-10-12
$Advanced Micro Devices(AMD)$
cloudwin
2022-11-19
此网友纯傻帽
国产显卡兼容NV CUDA 网友神评：成立2年的公司比AMD做得更好
cloudwin
2021-11-29
I would say you might always pick the wrong stock... Let wait and see...
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href=\"https://laohu8.com/S/NVDA\">英伟达</a>旗舰产品GB200 NVL72的超越，标志着中国在人工智能基础设施领域实现里程碑式突破。</p><img src=\"http://img.huanqiucdn.cn/dp/api/files/imageDir/547427798ee5e26025944afbbab32320.png?imageView2/2/w/1260\"/><p>据SemiAnalysis披露，华为云CM384基于384颗升腾芯片构建，通过全互连拓扑架构实现芯片间高效协同，可提供高达300 PFLOPs的密集BF16算力，接近达到英伟达GB200 NVL72系统的两倍。此外，CM384在内存容量和带宽方面同样占据优势，总内存容量超出英伟达方案3.6倍，内存带宽也达到2.1倍，为大规模AI训练和推理提供了更高效的硬件支持。</p><img src=\"http://img.huanqiucdn.cn/dp/api/files/imageDir/09a083332e306a64615059c6649521c0.png?imageView2/2/w/1260\"/><p>报道分析称，尽管单颗升腾芯片性能约为英伟达Blackwell架构GPU的三分之一，但华为通过规模化系统设计，成功实现整体算力跃升，并在超大规模模型训练、实时推理等场景中展现更强竞争力。SemiAnalysis也指出，华为的工程优势不仅体现在芯片层面，更在于系统级的创新，包括网络架构、光学互联和软件优化，使得CM384能够充分发挥集群算力，满足超大规模AI计算需求。</p><p>此次华为云CloudMatrix 384的发布，标志着中国在AI计算系统领域已具备与国际巨头正面竞争的实力。SemiAnalysis在报道中特别指出，华为的规模化解决方案“领先于英伟达和AMD目前市场上的产品一代”，并认为中国在AI基础设施上的突破将对全球AI产业格局产生深远影响。</p></article></body></html>","source":"tencent","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" 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}\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\n国际知名半导体研究机构SemiAnalysis称：华为云CloudMatrix 384领先英伟达和AMD的产品一代\n</h2>\n\n<h4 class=\"meta\">\n\n\n2025-04-25 17:30 北京时间 <a href=http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN202504251812169744dd0c&s=b><strong>中国日报网</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>近日，国际知名半导体研究和咨询机构SemiAnalysis发布专题报道称，华为云最新推出的AI算力集群解决方案CloudMatrix 384（以下简称CM384）凭借其颠覆性的系统架构设计与全栈技术创新，在多项关键指标上实现对英伟达旗舰产品GB200 NVL72的超越，标志着中国在人工智能基础设施领域实现里程碑式突破。据SemiAnalysis披露，华为云CM384基于384颗升腾芯片构建，通过全...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN202504251812169744dd0c&s=b\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"159582":"半导体","561980":"半导体设备ETF","AMD":"美国超微公司","NVDA":"英伟达"},"source_url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN202504251812169744dd0c&s=b","is_english":false,"share_image_url":"https://static.laohu8.com/9a95c1376e76363c1401fee7d3717173","article_id":"2530790275","content_text":"近日，国际知名半导体研究和咨询机构SemiAnalysis发布专题报道称，华为云最新推出的AI算力集群解决方案CloudMatrix 384（以下简称CM384）凭借其颠覆性的系统架构设计与全栈技术创新，在多项关键指标上实现对英伟达旗舰产品GB200 NVL72的超越，标志着中国在人工智能基础设施领域实现里程碑式突破。据SemiAnalysis披露，华为云CM384基于384颗升腾芯片构建，通过全互连拓扑架构实现芯片间高效协同，可提供高达300 PFLOPs的密集BF16算力，接近达到英伟达GB200 NVL72系统的两倍。此外，CM384在内存容量和带宽方面同样占据优势，总内存容量超出英伟达方案3.6倍，内存带宽也达到2.1倍，为大规模AI训练和推理提供了更高效的硬件支持。报道分析称，尽管单颗升腾芯片性能约为英伟达Blackwell架构GPU的三分之一，但华为通过规模化系统设计，成功实现整体算力跃升，并在超大规模模型训练、实时推理等场景中展现更强竞争力。SemiAnalysis也指出，华为的工程优势不仅体现在芯片层面，更在于系统级的创新，包括网络架构、光学互联和软件优化，使得CM384能够充分发挥集群算力，满足超大规模AI计算需求。此次华为云CloudMatrix 384的发布，标志着中国在AI计算系统领域已具备与国际巨头正面竞争的实力。SemiAnalysis在报道中特别指出，华为的规模化解决方案“领先于英伟达和AMD目前市场上的产品一代”，并认为中国在AI基础设施上的突破将对全球AI产业格局产生深远影响。","news_type":1},"isVote":1,"tweetType":1,"viewCount":11,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":254450257047800,"gmtCreate":1703158046933,"gmtModify":1703158047764,"author":{"id":"7435754264366302","authorId":"7435754264366302","name":"cloudwin","avatar":"https://static.tigerbbs.com/45019e99d1ed6c626d6131b00381047c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"idStr":"7435754264366302","authorIdStr":"7435754264366302"},"themes":[],"htmlText":"<a href=\"https://laohu8.com/S/NVDA\">$NVIDIA Corp(NVDA)$ </a>","listText":"<a href=\"https://laohu8.com/S/NVDA\">$NVIDIA Corp(NVDA)$ </a>","text":"$NVIDIA 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Devices(AMD)$","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/229711244992648","isVote":1,"tweetType":1,"viewCount":282,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":667234179,"gmtCreate":1668825666591,"gmtModify":1668826380081,"author":{"id":"7435754264366302","authorId":"7435754264366302","name":"cloudwin","avatar":"https://static.tigerbbs.com/45019e99d1ed6c626d6131b00381047c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"idStr":"7435754264366302","authorIdStr":"7435754264366302"},"themes":[],"htmlText":"此网友纯傻帽","listText":"此网友纯傻帽","text":"此网友纯傻帽","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/667234179","repostId":"2284724026","repostType":2,"repost":{"id":"2284724026","kind":"news","pubTimestamp":1668765869,"share":"https://www.laohu8.com/m/news/2284724026?lang=&edition=full","pubTime":"2022-11-18 18:04","market":"us","language":"zh","title":"国产显卡兼容NV CUDA 网友神评：成立2年的公司比AMD做得更好","url":"https://stock-news.laohu8.com/highlight/detail?id=2284724026","media":"快科技","summary":"摩尔线程是如何做到支持CUDA的呢？国产显卡能够兼容CUDA，这让部分网友非常意外，甚至有人神评——一家成立仅2年的GPU公司在CUDA支持上比AMD做得还要好，可见他们对这件事有多么震惊。当然，调侃贵调侃，说AMD不兼容CUDA也不是全对，实际上AMD显卡也跟可以摩尔线程显卡那样兼容CUDA，可以通过HIP来变相支持CUDA，但是AMD有自己的加速计算解决方案，不会把重点放在这方面。","content":"<html><body><p>前不久摩尔线程发布了发布了新一代游戏卡S80及加速卡S3000，不仅规格诱人，而且有几个地方很关键，那就是兼容CUDA计算。</p><p>用过计算卡的都知道CUDA意味着什么，NVIDIA的加速卡能够在AI及HPC计算领域大杀四方，核心优势就是CUDA，而AMD的加速卡不那么受欢迎，也不全是性能或者架构的问题，也是缺少类似CUDA这样的生态支持。</p><p><img src=\"http://x0.ifengimg.com/res/2022/BDE0E0229628206DC0004335F8AC56B6DF5E4737_size150_w600_h378.jpg\"/></p><p>摩尔线程是如何做到支持CUDA的呢？官方之前简单介绍了一下，<strong>他们开发了CUDA ON MUSA兼容方案，用户可以将CUDA上开发的代码无缝迁移到MTT S3000。</strong></p><p>具体的技术是如何实现的，摩尔线程并没有透露太多细节，不过这个功能也在国外引发了热议，因为大家都知道CUDA是NVIDIA的独家技术。</p><p><img src=\"http://x0.ifengimg.com/res/2022/302FC9313167A09D90B29F8437827A2C56C6F8BB_size45_w600_h248.png\"/></p><p>国产显卡能够兼容CUDA，这让部分网友非常意外，甚至有人神评——<strong>一家成立仅2年的GPU公司在CUDA支持上比AMD做得还要好，可见他们对这件事有多么震惊。</strong></p><p>当然，调侃贵调侃，说AMD不兼容CUDA也不是全对，实际上AMD显卡也跟可以摩尔线程显卡那样兼容CUDA，可以通过HIP来变相支持CUDA，但是AMD有自己的加速计算解决方案，不会把重点放在这方面。</p><p>对于摩尔线程来说，<strong>除了CUDA ON MUSA兼容方案之外，他们也会推自己的解决方案，</strong>这个过程需要时间。</p><p><img src=\"http://x0.ifengimg.com/res/2022/FF43DFB54F1E476848C8C4E94D259F9BA02B41DC_size110_w600_h388.jpg\"/></p></body></html>","source":"fenghuang_stock","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>国产显卡兼容NV CUDA 网友神评：成立2年的公司比AMD做得更好</title>\n<style 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margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\n国产显卡兼容NV CUDA 网友神评：成立2年的公司比AMD做得更好\n</h2>\n\n<h4 class=\"meta\">\n\n\n2022-11-18 18:04 北京时间 <a href=https://tech.ifeng.com/c/8L2rWbc7A1h><strong>快科技</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>前不久摩尔线程发布了发布了新一代游戏卡S80及加速卡S3000，不仅规格诱人，而且有几个地方很关键，那就是兼容CUDA计算。用过计算卡的都知道CUDA意味着什么，NVIDIA的加速卡能够在AI及HPC计算领域大杀四方，核心优势就是CUDA，而AMD的加速卡不那么受欢迎，也不全是性能或者架构的问题，也是缺少类似CUDA这样的生态支持。摩尔线程是如何做到支持CUDA的呢？官方之前简单介绍了一下，他们...</p>\n\n<a href=\"https://tech.ifeng.com/c/8L2rWbc7A1h\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"GFS":"GLOBALFOUNDRIES Inc.","LU1988902786.USD":"FULLERTON LUX FUNDS GLOBAL ABSOLUTE ALPHA \"I\" (USD) ACC","BK4529":"IDC概念","LU0082616367.USD":"摩根大通美国科技A（dist）","LU0719512351.SGD":"JPMorgan Funds - US Technology A (acc) SGD","BK4554":"元宇宙及AR概念","BK4532":"文艺复兴科技持仓","IE00BMPRXR70.SGD":"Neuberger Berman 5G Connectivity A Acc SGD-H","IE00BMPRXN33.USD":"NEUBERGER BERMAN 5G CONNECTIVITY \"A\" (USD) ACC","BK4534":"瑞士信贷持仓","BK4585":"ETF&股票定投概念","LU2264538146.SGD":"Fullerton Lux Funds - Global Absolute Alpha A Acc SGD","BK4566":"资本集团","BK4575":"芯片概念","AMD":"美国超微公司","LU1064131342.USD":"Fullerton Lux Funds - Global Absolute Alpha A Acc USD","BK4141":"半导体产品","LU1951198990.SGD":"Natixis Thematics AI & Robotics Fund H-R/A SGD-H","LU1951200564.SGD":"Natixis Thematics AI & Robotics Fund R/A SGD","BK4573":"虚拟现实","LU1923623000.USD":"Natixis Thematics AI & Robotics Fund R/A USD","BK4512":"苹果概念"},"source_url":"https://tech.ifeng.com/c/8L2rWbc7A1h","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2284724026","content_text":"前不久摩尔线程发布了发布了新一代游戏卡S80及加速卡S3000，不仅规格诱人，而且有几个地方很关键，那就是兼容CUDA计算。用过计算卡的都知道CUDA意味着什么，NVIDIA的加速卡能够在AI及HPC计算领域大杀四方，核心优势就是CUDA，而AMD的加速卡不那么受欢迎，也不全是性能或者架构的问题，也是缺少类似CUDA这样的生态支持。摩尔线程是如何做到支持CUDA的呢？官方之前简单介绍了一下，他们开发了CUDA ON MUSA兼容方案，用户可以将CUDA上开发的代码无缝迁移到MTT S3000。具体的技术是如何实现的，摩尔线程并没有透露太多细节，不过这个功能也在国外引发了热议，因为大家都知道CUDA是NVIDIA的独家技术。国产显卡能够兼容CUDA，这让部分网友非常意外，甚至有人神评——一家成立仅2年的GPU公司在CUDA支持上比AMD做得还要好，可见他们对这件事有多么震惊。当然，调侃贵调侃，说AMD不兼容CUDA也不是全对，实际上AMD显卡也跟可以摩尔线程显卡那样兼容CUDA，可以通过HIP来变相支持CUDA，但是AMD有自己的加速计算解决方案，不会把重点放在这方面。对于摩尔线程来说，除了CUDA ON MUSA兼容方案之外，他们也会推自己的解决方案，这个过程需要时间。","news_type":1},"isVote":1,"tweetType":1,"viewCount":970,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0},{"id":600403448,"gmtCreate":1638181552597,"gmtModify":1638181552597,"author":{"id":"7435754264366302","authorId":"7435754264366302","name":"cloudwin","avatar":"https://static.tigerbbs.com/45019e99d1ed6c626d6131b00381047c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"idStr":"7435754264366302","authorIdStr":"7435754264366302"},"themes":[],"htmlText":"I would say you might always pick the wrong stock... Let wait and see...","listText":"I would say you might always pick the wrong stock... Let wait and see...","text":"I would say you might always pick the wrong stock... Let wait and see...","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/600403448","repostId":"2186262293","repostType":2,"isVote":1,"tweetType":1,"viewCount":2064,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0}],"hots":[{"id":429277293633656,"gmtCreate":1745825748834,"gmtModify":1745825751560,"author":{"id":"7435754264366302","authorId":"7435754264366302","name":"cloudwin","avatar":"https://static.tigerbbs.com/45019e99d1ed6c626d6131b00381047c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"7435754264366302","idStr":"7435754264366302"},"themes":[],"htmlText":"Fake title","listText":"Fake title","text":"Fake title","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/429277293633656","repostId":"2530790275","repostType":2,"isVote":1,"tweetType":1,"viewCount":11,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":600403448,"gmtCreate":1638181552597,"gmtModify":1638181552597,"author":{"id":"7435754264366302","authorId":"7435754264366302","name":"cloudwin","avatar":"https://static.tigerbbs.com/45019e99d1ed6c626d6131b00381047c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"7435754264366302","idStr":"7435754264366302"},"themes":[],"htmlText":"I would say you might always pick the wrong stock... Let wait and see...","listText":"I would say you might always pick the wrong stock... Let wait and see...","text":"I would say you might always pick the wrong stock... Let wait and see...","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/600403448","repostId":"2186262293","repostType":2,"isVote":1,"tweetType":1,"viewCount":2064,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0},{"id":254450257047800,"gmtCreate":1703158046933,"gmtModify":1703158047764,"author":{"id":"7435754264366302","authorId":"7435754264366302","name":"cloudwin","avatar":"https://static.tigerbbs.com/45019e99d1ed6c626d6131b00381047c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"7435754264366302","idStr":"7435754264366302"},"themes":[],"htmlText":"<a href=\"https://laohu8.com/S/NVDA\">$NVIDIA Corp(NVDA)$ </a>","listText":"<a href=\"https://laohu8.com/S/NVDA\">$NVIDIA Corp(NVDA)$ </a>","text":"$NVIDIA Corp(NVDA)$","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/254450257047800","isVote":1,"tweetType":1,"viewCount":703,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":249136140767312,"gmtCreate":1701855029065,"gmtModify":1701855068914,"author":{"id":"7435754264366302","authorId":"7435754264366302","name":"cloudwin","avatar":"https://static.tigerbbs.com/45019e99d1ed6c626d6131b00381047c","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"7435754264366302","idStr":"7435754264366302"},"themes":[],"htmlText":"<a href=\"https://laohu8.com/S/AMD\">$Advanced Micro Devices(AMD)$ </a>","listText":"<a href=\"https://laohu8.com/S/AMD\">$Advanced Micro Devices(AMD)$ </a>","text":"$Advanced Micro 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18:04","market":"us","language":"zh","title":"国产显卡兼容NV CUDA 网友神评：成立2年的公司比AMD做得更好","url":"https://stock-news.laohu8.com/highlight/detail?id=2284724026","media":"快科技","summary":"摩尔线程是如何做到支持CUDA的呢？国产显卡能够兼容CUDA，这让部分网友非常意外，甚至有人神评——一家成立仅2年的GPU公司在CUDA支持上比AMD做得还要好，可见他们对这件事有多么震惊。当然，调侃贵调侃，说AMD不兼容CUDA也不是全对，实际上AMD显卡也跟可以摩尔线程显卡那样兼容CUDA，可以通过HIP来变相支持CUDA，但是AMD有自己的加速计算解决方案，不会把重点放在这方面。","content":"<html><body><p>前不久摩尔线程发布了发布了新一代游戏卡S80及加速卡S3000，不仅规格诱人，而且有几个地方很关键，那就是兼容CUDA计算。</p><p>用过计算卡的都知道CUDA意味着什么，NVIDIA的加速卡能够在AI及HPC计算领域大杀四方，核心优势就是CUDA，而AMD的加速卡不那么受欢迎，也不全是性能或者架构的问题，也是缺少类似CUDA这样的生态支持。</p><p><img src=\"http://x0.ifengimg.com/res/2022/BDE0E0229628206DC0004335F8AC56B6DF5E4737_size150_w600_h378.jpg\"/></p><p>摩尔线程是如何做到支持CUDA的呢？官方之前简单介绍了一下，<strong>他们开发了CUDA ON MUSA兼容方案，用户可以将CUDA上开发的代码无缝迁移到MTT S3000。</strong></p><p>具体的技术是如何实现的，摩尔线程并没有透露太多细节，不过这个功能也在国外引发了热议，因为大家都知道CUDA是NVIDIA的独家技术。</p><p><img src=\"http://x0.ifengimg.com/res/2022/302FC9313167A09D90B29F8437827A2C56C6F8BB_size45_w600_h248.png\"/></p><p>国产显卡能够兼容CUDA，这让部分网友非常意外，甚至有人神评——<strong>一家成立仅2年的GPU公司在CUDA支持上比AMD做得还要好，可见他们对这件事有多么震惊。</strong></p><p>当然，调侃贵调侃，说AMD不兼容CUDA也不是全对，实际上AMD显卡也跟可以摩尔线程显卡那样兼容CUDA，可以通过HIP来变相支持CUDA，但是AMD有自己的加速计算解决方案，不会把重点放在这方面。</p><p>对于摩尔线程来说，<strong>除了CUDA ON MUSA兼容方案之外，他们也会推自己的解决方案，</strong>这个过程需要时间。</p><p><img src=\"http://x0.ifengimg.com/res/2022/FF43DFB54F1E476848C8C4E94D259F9BA02B41DC_size110_w600_h388.jpg\"/></p></body></html>","source":"fenghuang_stock","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>国产显卡兼容NV CUDA 网友神评：成立2年的公司比AMD做得更好</title>\n<style 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}\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\n国产显卡兼容NV CUDA 网友神评：成立2年的公司比AMD做得更好\n</h2>\n\n<h4 class=\"meta\">\n\n\n2022-11-18 18:04 北京时间 <a href=https://tech.ifeng.com/c/8L2rWbc7A1h><strong>快科技</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>前不久摩尔线程发布了发布了新一代游戏卡S80及加速卡S3000，不仅规格诱人，而且有几个地方很关键，那就是兼容CUDA计算。用过计算卡的都知道CUDA意味着什么，NVIDIA的加速卡能够在AI及HPC计算领域大杀四方，核心优势就是CUDA，而AMD的加速卡不那么受欢迎，也不全是性能或者架构的问题，也是缺少类似CUDA这样的生态支持。摩尔线程是如何做到支持CUDA的呢？官方之前简单介绍了一下，他们...</p>\n\n<a href=\"https://tech.ifeng.com/c/8L2rWbc7A1h\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"GFS":"GLOBALFOUNDRIES Inc.","LU1988902786.USD":"FULLERTON LUX FUNDS GLOBAL ABSOLUTE ALPHA \"I\" (USD) ACC","BK4529":"IDC概念","LU0082616367.USD":"摩根大通美国科技A（dist）","LU0719512351.SGD":"JPMorgan Funds - US Technology A (acc) SGD","BK4554":"元宇宙及AR概念","BK4532":"文艺复兴科技持仓","IE00BMPRXR70.SGD":"Neuberger Berman 5G Connectivity A Acc SGD-H","IE00BMPRXN33.USD":"NEUBERGER BERMAN 5G CONNECTIVITY \"A\" (USD) ACC","BK4534":"瑞士信贷持仓","BK4585":"ETF&股票定投概念","LU2264538146.SGD":"Fullerton Lux Funds - Global Absolute Alpha A Acc SGD","BK4566":"资本集团","BK4575":"芯片概念","AMD":"美国超微公司","LU1064131342.USD":"Fullerton Lux Funds - Global Absolute Alpha A Acc USD","BK4141":"半导体产品","LU1951198990.SGD":"Natixis Thematics AI & Robotics Fund H-R/A SGD-H","LU1951200564.SGD":"Natixis Thematics AI & Robotics Fund R/A SGD","BK4573":"虚拟现实","LU1923623000.USD":"Natixis Thematics AI & Robotics Fund R/A USD","BK4512":"苹果概念"},"source_url":"https://tech.ifeng.com/c/8L2rWbc7A1h","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2284724026","content_text":"前不久摩尔线程发布了发布了新一代游戏卡S80及加速卡S3000，不仅规格诱人，而且有几个地方很关键，那就是兼容CUDA计算。用过计算卡的都知道CUDA意味着什么，NVIDIA的加速卡能够在AI及HPC计算领域大杀四方，核心优势就是CUDA，而AMD的加速卡不那么受欢迎，也不全是性能或者架构的问题，也是缺少类似CUDA这样的生态支持。摩尔线程是如何做到支持CUDA的呢？官方之前简单介绍了一下，他们开发了CUDA ON MUSA兼容方案，用户可以将CUDA上开发的代码无缝迁移到MTT S3000。具体的技术是如何实现的，摩尔线程并没有透露太多细节，不过这个功能也在国外引发了热议，因为大家都知道CUDA是NVIDIA的独家技术。国产显卡能够兼容CUDA，这让部分网友非常意外，甚至有人神评——一家成立仅2年的GPU公司在CUDA支持上比AMD做得还要好，可见他们对这件事有多么震惊。当然，调侃贵调侃，说AMD不兼容CUDA也不是全对，实际上AMD显卡也跟可以摩尔线程显卡那样兼容CUDA，可以通过HIP来变相支持CUDA，但是AMD有自己的加速计算解决方案，不会把重点放在这方面。对于摩尔线程来说，除了CUDA ON MUSA兼容方案之外，他们也会推自己的解决方案，这个过程需要时间。","news_type":1},"isVote":1,"tweetType":1,"viewCount":970,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0}],"lives":[]}
