NVIDIA Plans to Deploy 800,000 SOCAMM Modules in AI Products This Year

NVIDIA, the renowned GPU manufacturer, is making strides in expanding its inventory of the innovative modular memory solution known as SOCAMM (Scalable On-Demand AI Memory Module).This advancement is poised to facilitate seamless memory upgrades across AI devices, thereby enhancing overall performance and energy efficiency.

NVIDIA’s SOCAMM Memory Expansion: A Response to Rising Demand

Unveiled during the recent NVIDIA GTC event, the SOCAMM memory system is set to experience a notable increase in production throughout this year. This initiative comes as NVIDIA aims to deliver top-tier performance while minimizing power consumption in its artificial intelligence (AI) product lineup. During the event, attendees observed NVIDIA’s GB300 platform operating with SOCAMM memory, a component developed in collaboration with Micron. This solution differentiates itself from widely-used memory types like HBM and LPDDR5X, which are common in AI servers and mobile devices.

The SOCAMM memory utilizes LPDDR DRAM, traditionally favored for mobile and energy-efficient devices. However, a key distinguishing feature of SOCAMM is its modular design, allowing for upgrades—unlike other systems where memory is permanently soldered to the PCB. Reports from ETNews indicate that NVIDIA plans to manufacture between 600, 000 and 800, 000 SOCAMM units this year, emphasizing its commitment to enhancing its AI product range.

Among the early adopters of SOCAMM memory is the latest iteration of the GB300 Blackwell platform. This development signals NVIDIA’s shift toward adopting new memory form factors across its AI technological ecosystem. Although the anticipated production of up to 800, 000 SOCAMM units this year is modest compared to the HBM memory supplied by NVIDIA’s partners in 2025, further scaling is expected next year with the rollout of the SOCAMM 2 memory variant.

SOCAMM NVIDIA GB300 — Image Credit: servethehome.com

The SOCAMM memory introduces a specialized form factor that is not only compact and modular but also significantly enhances power efficiency compared to traditional RDIMM solutions. While the precise metrics on power efficiency remain under wraps, early reports suggest that SOCAMM promises higher bandwidth capabilities than RDIMM, along with superior performance compared to popular alternatives like LPDDR5X and LPCAMM utilized in mobile devices.

With expected memory bandwidth ranging from 150 to 250 GB/s, SOCAMM represents a flexible and upgradeable solution for AI PCs and servers. This innovation offers users the potential for easy enhancements, further establishing NVIDIA’s commitment to leading advancements in AI technology.

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