NVIDIA褰掓。 - 鐟炴妧绉戞妧 //tedxccu.net/tag/nvidia 一站式IT解决方案提供?/description> Wed, 26 Mar 2025 06:31:14 +0000 zh-Hans hourly 1 //wordpress.org/?v=6.8.3 //tedxccu.net/wp-content/uploads/2023/06/cropped-fav-32x32.png NVIDIA褰掓。 - 鐟炴妧绉戞妧 //tedxccu.net/tag/nvidia 32 32 NVIDIA褰掓。 - 鐟炴妧绉戞妧 //tedxccu.net/bytebridge-blog/weka-nvidia-blackwell-collaboration.html?utm_source=rss&utm_medium=rss&utm_campaign=weka-nvidia-blackwell-collaboration Tue, 25 Mar 2025 08:43:21 +0000 //tedxccu.net/?p=27464 NVIDIA GB200（Blackwell）平台正以前所未有的速度、规模和效率重塑 AI 计算。NVIDIA […]

WEKA 携手 NVIDIA Blackwell，释?AI 推理无限潜能最先出现在瑞技科技?/p> ]]>

NVIDIA GB200（Blackwell）平台正以前所未有?strong>速度、规模和效率重塑 AI 计算。NVIDIA Blackwell 专为满足下一?AI 工作负载的巨大需求而设计，在推理模型、AI 代理和 Token 生成等方面展现了突破性进展。凭借其先进的架构，Blackwell GPU 提供超高速通信、巨大的内存带宽以及无与伦比的计算能力，这些都是实现实时 AI 决策所必需的。随着 AI 从单纯的训练转向复杂的推理和决策，基础设施必须不断进化以跟上步伐?/p>

新型 AI 超级芯片
新型 AI 超级芯片
Blackwell 架构 GPU 拥有2080亿个晶体管，采用专门定制的台积电 4NP 工艺制造。所?Blackwell 产品均采用双倍光刻极限尺寸的裸片，通过 10 TB/s 的片间互联技术连接成一块统一?GPU?/span>

然而，仅靠强大?GPU 性能还远远不够?/p>

 

要充分释?AI 推理的潜力，云服务商还需要同样高性能的数据基础设施，以消除瓶颈并最大化资源利用率。这也是 WEKA 获得 NVIDIA GB200 高性能数据存储认证的重要原因，?NVIDIA 云合作伙伴（NCP）提供支持。使他们在构?AI 云、GPU 即服务或其他新一代云产品时，能够提供最快、最具扩展?/strong>的数据基础设施。该认证基于 WEKA 此前获得?NVIDIA HGX H100/H200 系统认证，并为与 Yotta、Ori Cloud、Sustainable Metal Cloud 等众多领先新型云服务商的长期合作带来更多价值?/p>

为什么这至关重要：AI 不仅更快，而是本质上不?/h2>

AI 的发展正经历深刻变革。随着推理模型?AI 代理的普及，AI 工作负载变得更加复杂，不仅需要高速通信、充足内存及强大计算能力，还要能够实时生成和处理海量数据 Tokens，这要求数据基础设施必须能够?GPU 高性能协同工作?/p>

 

但传统的数据存储在以下几方面存在严重短板?/p>

  • 性能鸿沟?/strong>传统存储无法满足现代 AI 工作负载的对 I/O 的高要求，计算与数据基础设施之间的高延迟导致 GPU 利用率不足?/li>
  • 扩展困境?/strong>许多服务商往往不得不过度配置存储来满足性能目标，从而大幅推高成本?/li>
  • 多租户支持不足：传统存储缺乏有效隔离机制，迫使服务商为每个客户建立低效的存储孤岛?/li>
  • 运维成本和复杂性高?/strong>基于复制的传统容灾模型进一步抬高了管理成本?/li>

WEKA + NVIDIA GB200 ：为 AI 时代量身打?/h2>

WEKA 现已获得 NVIDIA GB200 部署高性能存储认证，NCP 可利?WEKA 全面提升 AI 云服务能力：

  • 极致的性能?/strong>WEKA 零调优架构能动态适配任何工作负载，实现亚毫秒级延迟和百万?IOPS。单?8U 基础配置即可满足 GB200 Blackwell 可扩展集群（1,152?GPU）的极端 I/O 需求?/li>
  • 面向 AI 管道优化?S3 对象存储?/strong>WEKA 通过优化?S3 对象存储接口，为 AI、机器学习和数据分析工作负载中的小对象的访问提供超低延迟和高吞吐量支持?/li>
  • 最大化 GPU 利用率：存储瓶颈常常扼杀 AI 性能，?WEKA 能帮助消除这一障碍，使数据性能提升 10 倍或更多。在实际部署中，客户?GPU 利用率从 30-40% 跃升至超?90%?/li>
  • 真正的多租户支持?/strong>WEKA 的可组合集群利用容器技术实现逻辑与物理双重隔离，从而提供安全、高性能?AI 云多租户服务，实现性能零妥协?/li>
  • 大规模扩展能力：WEKA 在单一命名空间内可支持多达 32,000 ?NVIDIA GPU 集群，助力英伟达云合作伙伴在全球范围内实现从 PB ?EB 级的无缝扩展，而无需担心架构受限?/li>
  • 无缝迁移?/strong>无论是在数据中心、超大规模云还是新一代云环境，WEKA 统一的软件架构均可实现工作负载的无缝迁移?/li>

基准测试与实际性能表现

WEKApod Nitro 设备?NVIDIA 云合作伙伴部署提供了卓越的性能密度和能效：

WEKApod Nitro 设备
WEKApod Nitro 设备
  • 吞吐性能?/strong>WEKApod 单节点实?70GB/s 读取速度（最低配置下可达 560GB/s）和 40GB/s 写入速度（最低配置下可达 320GB/s），确保 Blackwell GPU 持续获得高速数据，最大化利用率?/li>
  • 延迟优化?/strong>亚毫秒级延迟，确?AI 训练和推理工作负载延迟最小化，助力实时推?AI 模型高效运行?/li>
  • 扩展性实践：借助 WEKApod，NCP 已实现从 PB 级到 EB 级的数据规模扩展，支持数千个并发工作负载而不牺牲性能?/li>
  • GPU 利用率提升：WEKA 的可组合集群利用容器技术实现逻辑与物理双重隔离，从而提供安全、高性能?AI 云多租户服务，实现性能零妥协?/li>
  • 能效优化?/strong>WEKApod 优化的数据处理显著降低了每个 AI 工作负载的能耗，?AI 云服务商降低了整体运营成本?/li>
  • NVIDIA 认证?/strong>WEKA 荣获 NVIDIA 系统存储解决方案认证，确保为 AI 和数据分析工作负载提供高性能、可扩展且可靠的存储解决方案?/li>

NVIDIA MGX 部署的推荐存储配?/h2>

合理的存储配置对确保 AI 训练和推理的最佳性能至关重要。存储性能目标因模型类型、数据集大小和工作负载特征而异。为支持 NVIDIA MGX 系统上的高性能训练和推理，WEKA Data Platform 提供了一?NVIDIA Blackwell 认证的、可扩展且高吞吐量的存储方案，完美契合现?AI 工作负载的需求?/p>

 

对于大规?AI 训练来说，检查点的读写性能尤为关键，这是一个同步任务，若优化不当，可能会导致训练停滞。大型语言模型（LLM）在检查点阶段需极高写入吞吐量，其需求也会随着模型规模增长而增加。例如，一?300 亿参数模型可能需?206 GB/s 的总写入速率，而一?1 万亿参数模型则可能需要近 389 GB/s 的写入速率?/p>

 

下表展示?WEKApod Nitro 设备在满?NVIDIA GB200 NVL72 机架（最低存储容?10,924TB）增强型指导/性能要求下的存储密度与认证性能?/p>

通过使用 WEKApod，云服务商可以彻底消除存储瓶颈，确保 Blackwell GPU 始终以最佳状态运行，而无需过度超配?/p>

未来已来：构?AI 推理时代的基础设施

AI 推理时代需要一种全新的数据基础设施，它不仅要运行快速、高效，还能应对 Token 经济的爆发式增长。现在，借助 WEKA ?NVIDIA GB200 NVL72 强强联手，AI 云服务商可以同时获得出色的性能、强大的扩展性和安全保障长?/p>

 

如果您是正在构建下一?AI 云服务的 NVIDIA 云合作伙伴，现在正是解锁 GPU 潜能的最佳时机，?WEKA 携手，让您的 AI 云服务更加快速、稳定、简单！

WEKA 携手 NVIDIA Blackwell，释?AI 推理无限潜能

联系瑞技

您正在为您的 AI 云服务寻找突破性的性能、弹性、可扩展性和数据灵活性吗？立即联系瑞技?/p>

WEKA 携手 NVIDIA Blackwell，释?AI 推理无限潜能最先出现在瑞技科技?/p> ]]> Supermicro 联手 NVIDIA Spectrum?X 推出针对 AI 优化的系?/title> <link>//tedxccu.net/bytebridge-blog/networking-hardware-devices-for-nvidia-spectrum-x.html?utm_source=rss&utm_medium=rss&utm_campaign=networking-hardware-devices-for-nvidia-spectrum-x</link> <dc:creator><![CDATA[BBT Partner Channel]]></dc:creator> <pubDate>Thu, 05 Dec 2024 02:22:36 +0000</pubDate> <category><![CDATA[blog]]></category> <category><![CDATA[AI]]></category> <category><![CDATA[NVIDIA]]></category> <category><![CDATA[Supermicro]]></category> <guid isPermaLink="false">//tedxccu.net/?p=26453</guid> <description><![CDATA[<p>AI 正在推动对更先进计算基础设施的需求，包括网络。网络带宽的不足常常成为驱动 AI 应用信息处理的瓶颈。计?[…]</p> <p><a href="//tedxccu.net/bytebridge-blog/networking-hardware-devices-for-nvidia-spectrum-x.html">Supermicro 联手 NVIDIA Spectrum?X 推出针对 AI 优化的系?/a>最先出现在<a href="//tedxccu.net">瑞技科技</a>?/p> ]]></description> <content:encoded><![CDATA[ <div data-elementor-type="wp-post" data-elementor-id="26453" class="elementor elementor-26453" data-elementor-post-type="post"> <section class="elementor-section elementor-top-section elementor-element elementor-element-53ffd14 elementor-section-boxed elementor-section-height-default elementor-section-height-default" data-id="53ffd14" data-element_type="section" data-settings="{"ekit_has_onepagescroll_dot":"yes"}"> <div id="1znm7tie1g" class="elementor-container elementor-column-gap-default"> <div class="elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-36abd74" data-id="36abd74" data-element_type="column"> <div id="1znm7tie1g" class="elementor-widget-wrap elementor-element-populated"> <div class="elementor-element elementor-element-de37c7a elementor-widget elementor-widget-text-editor" data-id="de37c7a" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="text-editor.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <p>AI 正在推动对更先进计算基础设施的需求，包括网络。网络带宽的不足常常成为驱动 AI 应用信息处理的瓶颈。计算基础设施的速度仅取决于其最弱环节，而这个环节往往就是网络。通过与NVIDIA合作?a href="/supermicro" target="_blank" rel="noopener"><span style="text-decoration: underline;">Supermicro</span></a> 已经在其多个系统中验证了新的 NVIDIA Spectrum-X 网络平台，允许AI 工作负载的网络性能提高多达1.6倍，同时增加能效并降低总体成本。结?NVIDIA Spectrum-4以太网交换机?NVIDIA BlueField®-3 SuperNIC，客户现在可以最大化 AI 云处理基础设施的性能?/p><p><br />目前正在验证配备 NVIDIA Spectrum-X 网络解决方案的系统包?Supermicro 明星 GPU 超级服务器，包括4U?U?U，并支持以下系统中的 NVIDIA GPU?/p> </div> </div> <div class="elementor-element elementor-element-38ae6b7 elementor-widget elementor-widget-spacer" data-id="38ae6b7" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="spacer.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <div id="1znm7tie1g" class="elementor-spacer"> <div id="1znm7tie1g" class="elementor-spacer-inner"></div> </div> </div> </div> <div class="elementor-element elementor-element-a817dbb elementor-widget elementor-widget-text-editor" data-id="a817dbb" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="text-editor.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <ul><li><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":180,"335559740":360}"> </span><span data-contrast="none">搭载 </span><span data-contrast="none">NVIDIA HGX H100 8-GPU</span><span data-contrast="none"> 系统?</span><span data-contrast="none">Supermicro 8U GPU</span><span data-contrast="none"> 服务器：</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li></ul><ol><li><span data-contrast="none">SYS-821GE-TNHR (8U)</span><span data-contrast="none"> ?</span><span data-contrast="none">Intel CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li><li><span data-contrast="none">AS-8125GS-TNHR (8U) ?AMD CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li><li><span data-contrast="none">SYS-421GU-TNXR (4U)</span><span data-contrast="none"> ?</span><span data-contrast="none">Intel CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li></ol><ul><li><span data-contrast="none">搭载 </span><span data-contrast="none">NVIDIA H100 PCIe GPU</span><span data-contrast="none"> ?</span><span data-contrast="none">NVIDIA L40S GPU</span><span data-contrast="none"> ?</span><span data-contrast="none">Supermicro</span><span data-contrast="none"> 通用 </span><span data-contrast="none">GPU</span><span data-contrast="none"> 服务器（4U?U）：</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li></ul><ol><li><span data-contrast="none">SYS-521GE-TNRT (5U)</span><span data-contrast="none"> ?</span><span data-contrast="none">Intel CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li><li><span data-contrast="none">SYS-421GE-TNRT (4U)</span><span data-contrast="none"> ?</span><span data-contrast="none">Intel CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li><li><span data-contrast="none">SYS-421GE-TNRT3 (4U)</span><span data-contrast="none"> ?</span><span data-contrast="none">Intel CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li><li><span data-contrast="none">AS-4125GS-TNRT (4U)</span><span data-contrast="none"> ?</span><span data-contrast="none">AMD CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li><li><span data-contrast="none">AS-4125GS-TNRT2 (4U) ?AMD CPU</span><span data-ccp-props="{"134233117":false,"134233118":false,"134245417":false,"201341983":0,"335551550":6,"335551620":6,"335557856":16777215,"335559738":0,"335559739":0,"335559740":360}"> </span></li></ol> </div> </div> <div class="elementor-element elementor-element-66b93b2 elementor-widget elementor-widget-spacer" data-id="66b93b2" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="spacer.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <div id="1znm7tie1g" class="elementor-spacer"> <div id="1znm7tie1g" class="elementor-spacer-inner"></div> </div> </div> </div> <div class="elementor-element elementor-element-96e61ec elementor-widget elementor-widget-image" data-id="96e61ec" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="image.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <img decoding="async" width="980" height="276" src="//tedxccu.net/wp-content/uploads/2024/12/data-centers-ai-optimized-nvidia-spectrum-x-2.webp" class="attachment-large size-large wp-image-26456" alt="配备 NVIDIA Spectrum-X 网络解决方案?Supermicro 明星 GPU 超级服务? srcset="//tedxccu.net/wp-content/uploads/2024/12/data-centers-ai-optimized-nvidia-spectrum-x-2.webp 992w, //tedxccu.net/wp-content/uploads/2024/12/data-centers-ai-optimized-nvidia-spectrum-x-2-300x84.webp 300w, //tedxccu.net/wp-content/uploads/2024/12/data-centers-ai-optimized-nvidia-spectrum-x-2-768x216.webp 768w" sizes="(max-width: 980px) 100vw, 980px" /> </div> </div> <div class="elementor-element elementor-element-b0c3adb elementor-widget elementor-widget-spacer" data-id="b0c3adb" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="spacer.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <div id="1znm7tie1g" class="elementor-spacer"> <div id="1znm7tie1g" class="elementor-spacer-inner"></div> </div> </div> </div> <div class="elementor-element elementor-element-e4a9aec elementor-widget elementor-widget-text-editor" data-id="e4a9aec" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="text-editor.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <p>这些?NVIDIA Spectrum-X 驱动?Supermicro 系统减少了基于大型变换器的生成式 AI 模型的训练和推理时间，这对于?AI 中快速获得数据至关重要?/p><p><br />除了?AI 极大提高1.6倍的网络性能外，配备 NVIDIA Spectrum-X 网络?Supermicro 系统还从多租户环境中隔离工作负载性能中受益。允许工作负载独立于移动数据，不受可能阻碍性能的“嘈杂邻居”干扰，这对于高性能应用至关重要。此外，隔离网络工作负载还提供了额外的安全优势，可以防止一个工作负载中的恶意行为者干扰另一个独立的工作负载。NVIDIA Spectrum-X 通过为每个租户分配安全的虚拟私有云（VPCs）来实现这种增强的工作负载隔离?/p><p><br />能效一直是运行高性能、高功率 AI 系统时的主要关注点。通过在相同的网络功耗范围内提供更好的网络性能，NVIDIA Spectrum-X 可以为更节能?AI 环境做出贡献，从而降低整体功耗和总体拥有成本。对于控制能源成本的用户，配?Spectrum-X ?Supermicro 系统是一个不错的选择?/p><p><br />NVIDIA Spectrum-X 完全基于标准设计，并且与基于以太网的堆栈可以实现完全互操作。此外，配备 NVIDIA Spectrum-X ?Supermicro 服务器可以帮助客户克服部?AI 的最大挑战——可扩展性。凭借在单个交换机中支持256?00G端口或在两层?脊拓扑中支持16K端口的能力，这些系统非常适合需要不断扩展基础设施的组织?/p><p><br />随着 Supermicro 努力满足不仅需要高性能网络而且需要云多租户的 AI 客户的需求，新系统利用远程直接内存访问（RDMA）、收敛以太网（RoCE）扩展来支持性能和多租户。与传统以太网相比，其性能大幅增长?/p><p><br />对于需要更快获得关键数据、多租户和未来可扩展性的客户，这些配?NVIDIA Spectrum-X 的Supermicro 系统非常适合他们的需求?/p> </div> </div> <div class="elementor-element elementor-element-ce2f618 elementor-widget elementor-widget-spacer" data-id="ce2f618" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="spacer.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <div id="1znm7tie1g" class="elementor-spacer"> <div id="1znm7tie1g" class="elementor-spacer-inner"></div> </div> </div> </div> <div class="elementor-element elementor-element-c9838e9 elementor-widget-divider--view-line elementor-widget elementor-widget-divider" data-id="c9838e9" data-element_type="widget" data-settings="{"ekit_we_effect_on":"none"}" data-widget_type="divider.default"> <div id="1znm7tie1g" class="elementor-widget-container"> <div id="1znm7tie1g" class="elementor-divider"> <span 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