[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"content-doc-dciobcbf0d7f":3},{"user":4,"document":8,"mainDocument":27,"columnUrl":29,"subscription":30,"footer":42,"text":77},{"isAuthenticated":5,"isAdmin":5,"displayName":6,"avatarUrl":6,"nid":6,"groupLevel":7},false,"",-10,{"id":9,"fullTitle":10,"subTitle":6,"url":11,"columnId":12,"columnName":13,"columnUrl":14,"summary":6,"contentHtml":15,"mainContentHtml":6,"posterUrl":16,"createDate":17,"displayDate":18,"displayDateSlash":19,"pageviews":20,"tags":21,"hidden":5,"isSubContent":5,"replyDocOrTargetId":6,"contentType":23,"videoId":6,"liveVideoUrl":6,"duration":24,"price":24,"priceText":25,"priceBadgeText":25,"priceBadgeClass":26,"freeForMinGroupLevel":24,"redirectUrl":6,"readyToStream":5},"dciobcbf0d7f","什么是 CXL？谷歌和英伟达青睐的替代内存技术","\u002Fdoc\u002Fdciobcbf0d7f","col18178739ee","美股资讯","\u002Fcol\u002Fcol18178739ee","\u003Cp>\u003Cspan style=\"font-family: DengXian; font-size: large;\">全球内存芯片短缺在人工智能热潮中再次凸显。\u003C\u002Fspan>\u003Cbr \u002F>\u003Cspan style=\"font-size: large;\"> \u003Cspan style=\"font-family: DengXian;\">随着\u003C\u002Fspan> AI \u003Cspan style=\"font-family: DengXian;\">服务器需求的激增，传统内存的供应逐渐成为限制系统性能的瓶颈，这促使科技公司开始寻找新的解决方案。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">一种被称为\u003C\u002Fspan>\u003Cstrong>Compute Express Link\u003C\u002Fstrong>\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">（\u003C\u002Fspan>CXL\u003C\u002Fstrong>\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">）\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan style=\"font-family: DengXian;\">的技术，近年来逐渐受到关注。\u003C\u002Fspan>\u003C\u002Fspan>\u003Cspan style=\"font-size: large;\">CXL \u003Cspan style=\"font-family: DengXian;\">是一种高速互连技术，能够让\u003C\u002Fspan> CPU\u003Cspan style=\"font-family: DengXian;\">、\u003C\u002Fspan>GPU \u003Cspan style=\"font-family: DengXian;\">以及内存设备之间进行更加高效的数据通信。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">在传统架构中，内存通常直接连接到\u003C\u002Fspan> CPU\u003Cspan style=\"font-family: DengXian;\">，并受到主板插槽数量和物理容量的限制。\u003C\u002Fspan>\u003C\u002Fspan>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">而\u003C\u002Fspan> CXL \u003Cspan style=\"font-family: DengXian;\">技术允许服务器从其他设备甚至其他服务器中\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">借用\u003C\u002Fspan>”\u003Cspan style=\"font-family: DengXian;\">内存，从而突破传统限制。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-family: DengXian; font-size: large;\">这种架构可以让数据中心更加灵活地分配内存资源。\u003C\u002Fspan>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">当某个服务器需要更多内存时，可以通过\u003C\u002Fspan> CXL \u003Cspan style=\"font-family: DengXian;\">网络访问共享内存池，而无需增加本地内存模块。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">随着\u003C\u002Fspan> AI \u003Cspan style=\"font-family: DengXian;\">模型规模不断扩大，对内存容量和带宽的需求持续增长。\u003C\u002Fspan>\u003C\u002Fspan>\u003Cspan style=\"font-family: DengXian; font-size: large;\">大型语言模型和深度学习系统需要处理海量数据，这使得内存成为影响性能的关键因素之一。\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp>\u003Cspan face=\"DengXian\" size=\"4\" style=\"font-family: DengXian; font-size: large;\">深度报告剩余80%内容，请登录官网 美股大数据  \u003Cspan style=\"font-family: DengXian; font-size: large;\">StockWe.com\u002Fdoc\u002Fdciob6d56ef0\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>","https:\u002F\u002Fwww.tradesmax.com\u002Fimages\u002Fa_Stock\u002FM\u002FMU\u002FMU.jpg","2026-03-12T19:43:15","2026.03.12","2026\u002F03\u002F12",47727,[22],"MU","Article",0,"免费","success",{"id":9,"fullTitle":10,"subTitle":6,"url":11,"columnId":12,"columnName":13,"columnUrl":14,"summary":6,"contentHtml":15,"mainContentHtml":6,"posterUrl":16,"createDate":17,"displayDate":18,"displayDateSlash":19,"pageviews":20,"tags":28,"hidden":5,"isSubContent":5,"replyDocOrTargetId":6,"contentType":23,"videoId":6,"liveVideoUrl":6,"duration":24,"price":24,"priceText":25,"priceBadgeText":25,"priceBadgeClass":26,"freeForMinGroupLevel":24,"redirectUrl":6,"readyToStream":5},[22],"\u002Fcol\u002Fstocknews",{"visible":5,"marketingHtml":31,"services":32,"recentDocuments":41},"\u003Cfigure class=\"image\">\u003Ca href=\"https:\u002F\u002Fstockwe.com\u002Fdoc\u002Fdcio537efad5\" target=\"_blank\" rel=\"noopener noreferrer\">\u003Cimg style=\"display:block;margin-left:auto;margin-right:auto;\" src=\"https:\u002F\u002Fstockwewebfiles.blob.core.windows.net\u002Fweb-202408-stk\u002F1586109431mceclip0.jpg\">\u003C\u002Fa>\u003C\u002Ffigure>\u003Cdiv class=\"text-center\">\u003Ch2 class=\"card-title mx-auto\">\u003Cbr>\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https:\u002F\u002Fstockwe.com\u002Fdoc\u002Fdcio537efad5\">案例介绍：英伟达深度研究报告\u003C\u002Fa>\u003C\u002Fh2>\u003C\u002Fdiv>",[33,37],{"productId":34,"serviceName":35,"priceText":36},"prod_PPxdDdK87QaiLv","月付","$12.95美元",{"productId":38,"serviceName":39,"priceText":40},"prod_PPxeMs3bix1da5","年付","$149.00美元",[],{"links":43,"images":68,"summaryHtml":73,"aboutTitle":74,"aboutHtml":75,"copyrightHtml":76},[44,47,50,53,56,59,62,65],{"label":45,"url":46},"深度报告","\u002Fcol\u002FdepthReport",{"label":48,"url":49},"VIP会员","\u002Fplan",{"label":51,"url":52},"期权推荐","\u002FOption",{"label":54,"url":55},"低价暴涨股","\u002FPenny",{"label":57,"url":58},"常见问题","https:\u002F\u002Fstockwe.com\u002FFAQ",{"label":60,"url":61},"美股课程","\u002Fcol\u002Fvideos",{"label":63,"url":64},"免责声明","\u002Fdisclaimer",{"label":66,"url":67},"联系我们","\u002FContactUs",[69,70,71,72],"https:\u002F\u002Fstockwebsiteblob.blob.core.windows.net\u002Fweb-202509-stk\u002FUploaderzic2tuwsol2_2025_09_11_18_21_07.gif","https:\u002F\u002Fstockwebsiteblob.blob.core.windows.net\u002Fweb-202509-stk\u002FUploadercakzdvydksw_2025_09_03_09_00_56.png","https:\u002F\u002Fstockwebsiteblob.blob.core.windows.net\u002Fweb-202509-stk\u002FUploadergtjyagwvoyk_2025_09_14_08_32_05.png","https:\u002F\u002Fstockwebsiteblob.blob.core.windows.net\u002Fweb-202509-stk\u002FUploader3u0tt4jhlqh_2025_09_23_22_30_48.png","邮箱: buy@TradesMax.com 美国电话 626-378-3637","公司介绍","\u003Cp class=\"MsoNormal\">美股大数据 StockWe.com 是一个美国领先的金融和美股信息大数据提供商，紧盯华尔街金融市场和行情，2008年成立于美国硅谷，创始人是前纽约证券交易所资深分析师Ken，联合多位摩根斯坦利分析师，谷歌 Meta工程师利用AI和大数据，配合十多年美股实战经验和业内量化交易模型，每天处理千万级股票数据：挖掘潜力大牛股，捕捉期权异动大单，实时主力资金流向、机构持仓变化、川普突发新闻，精准买卖信号第一时间发到您手机APP。\u003C\u002Fp>","专业美股投资者都在这里",{"loading":78,"search":79,"searchPlaceholder":79,"hotContent":80,"draft":81,"noData":82,"searchNoData":83,"edit":84,"editVideo":85,"courseContent":86,"more":87,"buyNow":88,"subscribeNow":89,"encoding":90,"paidContent":91},"Loading...","搜索","热门内容","草稿","目前没有任何内容公布","当前检索内容没有数据","编辑","编辑视频","课程内容","更多","立即购买后观看","- 立即订阅 -","视频编码中...","付费内容"]