NVIDIA 发布 NVHBM 定制高带宽内存，扩展 NVLink Fusion
NVIDIA NVLink Fusion Expands With NVHBM Custom High-Bandwidth Memory
The next wave of AI is placing new demands on infrastructure.
AI的下一波浪潮正在对基础设施提出新的要求。
As AI agents and trillion-parameter workloads become mainstream, the performance of AI infrastructure depends not only on compute, but on how compute, memory, storage, networking and software are designed together as a unified system.
随着AI代理和万亿参数工作负载成为主流，AI基础设施的性能不仅取决于计算能力，还取决于计算、内存、存储、网络和软件如何作为一个统一系统协同设计。
To help hyperscalers and AI innovators build the next generation of semi-custom AI infrastructure, NVIDIA today expanded NVIDIA NVLink Fusion with NVIDIA NVHBM, a next-generation high-bandwidth memory technology that brings higher memory performance and efficiency to XPUs. It will be validated and offered by leading memory partners, extending this advanced memory capability to NVLink Fusion customers.
为了帮助超大规模企业和AI创新者构建下一代半定制AI基础设施，NVIDIA今日扩展了NVIDIA NVLink Fusion，推出NVIDIA NVHBM——一种下一代高带宽内存技术，为XPU带来更高的内存性能和效率。该技术将由领先的内存合作伙伴验证并提供，将这一先进内存能力扩展到NVLink Fusion客户。
Traditional HBM architectures place the memory controller on the XPU die, consuming valuable silicon area that could otherwise be dedicated to compute. NVHBM, built on the same technology that NVIDIA will use for future GPUs, integrates NVIDIA’s custom memory controller into the HBM base die.
传统HBM架构将内存控制器置于XPU芯片上，消耗了宝贵的硅面积，这些面积本可用于计算。NVHBM基于NVIDIA未来GPU将使用的相同技术，将NVIDIA定制内存控制器集成到HBM基础芯片中。
By integrating the memory controller into the 3D HBM stack instead of the XPU, NVHBM delivers up to 30% greater memory bandwidth and 15% lower HBM power consumption, and frees up to 25% more area on XPU compute die compared with standard HBM4E.
通过将内存控制器集成到3D HBM堆栈中而非XPU上，与标准HBM4E相比，NVHBM可提供高达30%的内存带宽提升、15%的HBM功耗降低，并释放XPU计算芯片上多达25%的面积。
NVIDIA is establishing a standard NVHBM implementation, available from multiple memory providers. This reduces the engineering effort required to integrate and qualify memory across multiple suppliers — giving NVLink Fusion customers a faster path for bringing custom AI chips to market.
NVIDIA正在建立标准的NVHBM实现，可由多家内存供应商提供。这减少了跨多个供应商集成和认证内存所需的工程工作量，为NVLink Fusion客户提供了将定制AI芯片更快推向市场的途径。
Amazon’s Annapurna Labs will be the first to work on NVHBM as part of its broader collaboration with NVIDIA around NVLink Fusion.
亚马逊的Annapurna Labs将成为首个参与NVHBM工作的公司，作为其与NVIDIA在NVLink Fusion上更广泛合作的一部分。
AWS and NVIDIA Continue NVLink Fusion Collaboration
AWS与NVIDIA继续NVLink Fusion合作
Amazon’s Annapurna Labs will work with NVIDIA on NVHBM technology and the NVLink scale-up architecture to enhance performance and efficiency for AI workloads.
亚马逊的Annapurna Labs将与NVIDIA合作开发NVHBM技术和NVLink扩展架构，以提升AI工作负载的性能和效率。
This builds on AWS’s previously announced support for NVLink Fusion. Annapurna Labs will support NVLink Fusion with its next-generation Trainium chips starting with Trainium4, which would allow Amazon chips and NVIDIA GPUs to work together with common rack-scale architecture.
这建立在AWS先前宣布支持NVLink Fusion的基础上。Annapurna Labs将支持其下一代Trainium芯片（从Trainium4开始）上的NVLink Fusion，这将使亚马逊芯片和NVIDIA GPU能够以共同的机架级架构协同工作。
“NVHBM represents a new architectural approach to advancing high-bandwidth memory performance and efficiency,” said Nafea Bshara, vice president of Annapurna Labs at Amazon. “We look forward to this technology collaboration to benefit future AWS infrastructure designs.”
“NVHBM代表了一种推进高带宽内存性能和效率的新架构方法，”亚马逊Annapurna Labs副总裁Nafea Bshara表示。“我们期待这项技术合作能惠及未来的AWS基础设施设计。”
Vertically Integrated and Horizontally Open
垂直集成与水平开放
NVLink Fusion enables partners to connect custom XPUs and CPUs to NVIDIA’s rack-scale platform.
NVLink Fusion使合作伙伴能够将定制XPU和CPU连接到NVIDIA的机架级平台。
Partners can access NVIDIA NVLink chiplets, NVLink-C2C, NVLink Switches and NVIDIA MGX systems and racks, as well as a broad ecosystem of CPU partners, ASIC designers, system manufacturers and technology providers.
合作伙伴可以访问NVIDIA NVLink芯片、NVLink-C2C、NVLink交换机和NVIDIA MGX系统及机架，以及广泛的CPU合作伙伴、ASIC设计者、系统制造商和技术提供商生态系统。
Offered with each generation of NVIDIA’s rack-scale system architecture, NVLink Fusion allows hyperscalers and AI-native companies to focus engineering resources on XPU innovation while using a proven technology stack for scale-up and scale-out networking, rack-scale systems and software — creating a faster, lower-risk path to deploying semi-custom AI infrastructure.
随着NVIDIA每一代机架级系统架构的推出，NVLink Fusion允许超大规模企业和AI原生公司将工程资源集中于XPU创新，同时利用经过验证的技术栈进行扩展和横向扩展网络、机架级系统及软件——为部署半定制AI基础设施创造更快、更低风险的路径。
Learn more about NVLink and NVLink Fusion.
了解更多关于NVLink和NVLink Fusion的信息。
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