EE Times原文发布 08-04 03:00Radar 收录 08-04 03:31

瑞萨通过MRDIMM更新解决内存瓶颈

Renesas Tackles Memory Bottleneck with MRDIMM Update

中文摘要

瑞萨推出第三代DDR5 MRDIMM，带宽达16,000 MT/s，旨在解决AI内存瓶颈，无需平台大改。该产品面向AI应用，与元器件供应链相关。

原文深度解读

本文报道瑞萨电子推出第三代DDR5 MRDIMM芯片组解决方案，带宽高达16,000 MT/s，较上一代提升25%，旨在解决AI数据中心、云基础设施和高性能计算中的内存瓶颈。文章引用瑞萨产品管理总监Allen Youssefi的观点，强调该方案利用现有DDR5生态系统，无需重大平台改动即可提升性能，并改善每瓦性能。同时提及竞争对手Rambus的DDR5 9600服务器RDIMM芯片组。文章与电子元器件供应链相关，涉及内存接口芯片、服务器平台和AI基础设施。

瑞萨电子推出第三代DDR5 MRDIMM芯片组，带宽高达16,000 MT/s，比第二代提升25%。
该芯片组利用现有DDR5基础设施，保持标准机械和电气接口，部署主要是平台验证而非重大重新设计。
瑞萨产品管理总监Allen Youssefi表示，内存是AI和HPC系统的主要瓶颈，带宽提升未跟上计算能力增长。
MRDIMM通过允许CPU同时访问两个rank，相比传统RDIMM使数据速率和吞吐量翻倍。
瑞萨的Gen 3 MRDIMM芯片组是一个平台，包括MRCD、MDB、PMIC、SPD集线器和温度传感器。
Rambus最近宣布推出DDR5 9600服务器RDIMM芯片组，基于第六代寄存器时钟驱动器（RCD06），带宽比上一代提升20%。

供应链影响

瑞萨的MRDIMM芯片组可能推动服务器OEM采用该技术，从而影响内存接口芯片和DRAM模块的供应链需求。
由于MRDIMM利用现有DDR5生态系统，可能降低平台升级的硬件更换成本，但取决于OEM的验证和采纳速度。
AI推理工作负载的增长可能增加对高带宽内存解决方案的需求，进而影响相关芯片组和DRAM的采购量。
Rambus与瑞萨的竞争可能促进内存接口芯片市场的技术迭代，但市场份额变化取决于产品性能和客户选择。
每瓦性能的提升可能使数据中心更倾向于采用MRDIMM，但实际部署取决于功耗和散热约束的平衡。

系统解读，仅作为判断线索，不构成备货、出货、涨价或投资建议。

正文内容 · AI翻译

中文英文

人工智能数据中心、云基础设施和加速计算工作负载是瑞萨电子最新DDR5多路复用双列直插式内存模块（MRDIMM）芯片组开发的驱动因素。

“随着AI训练、AI推理、云计算和HPC工作负载持续扩展，处理器越来越受到内存数据传递速率的限制，”瑞萨内存接口部门产品管理总监Allen Youssefi在简报中告诉EE Times。

瑞萨的第三代DDR5 MRDIMM芯片组解决方案提供服务器级速度——高达16,000兆传输/秒（MT/s），内存带宽比公司第二代芯片组高25%。Youssefi表示，由于最新迭代利用现有DDR5基础设施，服务器平台可以在不进行破坏性架构更改的情况下提取更多性能。

瑞萨的第三代DDR5 MRDIMM芯片组解决方案提供高达16,000 MT/s的速度，内存带宽比上一代高25%。（来源：瑞萨）

Youssefi表示，这允许在不破坏服务器OEM已经依赖的平台模型的情况下扩展带宽。“MRDIMM使用相同的DDR5生态系统，并保持相同的标准机械和电气接口，”他说。“部署在很大程度上成为平台验证工作，而不是重大重新设计或硬件更换。”

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Youssefi表示，内存仍然是AI和HPC系统的主要瓶颈，因为带宽改进没有跟上计算能力的增长速度。“内存正在成为约束，而不是计算能力本身。”

随着数据中心从以训练为中心的AI周期转向推理时代，内存瓶颈的影响更加严重。“这些应用带有大规模模型、大规模参数和需要内存的数据，”Youssefi说。

在推理过程中，延迟直接影响用户体验，无论是解锁设备、在叫车应用中选择司机，还是服务实时企业工作负载。他说，更快地提供这些服务需要基础设施要求。“该基础设施依赖于CPU、GPU、计算引擎、机器学习模型和深度学习模型来支持推理。”

向更多推理密集型AI的转变发生在每瓦性能成为数据中心关键指标的时候，Youssefi表示这是瑞萨MRDIMM芯片组的另一个卖点。

他说，MRDIMM通过提供更高的内存带宽和更低的延迟来提高每瓦性能，而无需DRAM芯片以更高速度运行。由于DRAM不必超频，系统可以在大致相同的内存功耗下做更多有用工作，Youssefi说。

瑞萨的发布呼应了这一强调，称第三代设计时考虑了系统级电源效率，因为客户在更高带宽与热和功耗限制之间取得平衡。对于半导体工程师来说，更高带宽和受控功耗的结合可能是关键设计点，尤其是在内存通常是限制子系统的AI服务器中。

瑞萨的第三代DDR5 MRDIMM芯片组是一个平台，而不是单一的芯片对。Youssefi表示，公司的产品组合独特地定位于通过MRCD、MDB、PMIC、SPD集线器和温度传感器完成内存接口堆栈。

通过允许CPU同时访问两个rank，MRCD有效地将数据速率和吞吐量与传统RDIMM相比翻倍。（来源：瑞萨）

瑞萨并不是唯一一家使用DIMM技术解决内存瓶颈的公司。Rambus最近宣布推出其DDR5 9600服务器RDIMM芯片组，围绕其新的Rambus第六代寄存器时钟驱动器（RCD06）构建。该芯片组声称带宽比上一代提高20%，使RDIMM能够以高达9,600 MT/s的速度运行。

与瑞萨一样，Rambus希望提高带宽和容量，以支持代理AI、HPC和其他数据密集型工作负载。

Youssefi表示，如果AI和HPC需求继续按预期上升，这种增量但架构性的带宽增益可能比全面平台重新设计更有价值。“内存带宽已成为AI、HPC和云计算环境中最重要的约束之一。”

另请阅读：

动态AI需求推动内存多样性

加拿大AI生态系统需要更多紧迫性

国防向加拿大半导体行业发出明确信号

AI和大数据、高性能计算（HPC）、内存、MRDIMM

瑞萨电子

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Artificial intelligence data centers, cloud infrastructure, and accelerated compute workloads are the driving factors behind the development of Renesas Electronics’ latest DDR5 multiplexed rank dual in‑line memory module (MRDIMM) chipset.

“As AI training, AI inference, cloud computing, and HPC workloads continue to scale, processors are becoming increasingly limited by the rate at which data can be delivered from memory,” Allen Youssefi, director of product management for Renesas’ memory interface division, told EE Times in a briefing.

Renesas’ Gen 3 DDR5 MRDIMM chipset solutions deliver server-class speeds—up to 16,000 mega transfers per second (MT/s) and 25% higher memory bandwidth than the company’s Gen 2 chipsets. Youssefi said that because the latest iteration uses existing DDR5 infrastructure, server platforms can extract more performance without disruptive architectural changes.

Renesas’s Gen 3 DDR5 MRDIMM chipset solutions deliver up to 16,000 MT/s and 25% higher memory bandwidth than the company’s previous generation. (Source: Renesas)

Youssefi said this allows for scaling bandwidth without breaking the platform model that server OEMs already rely on. “MRDIMM uses the same DDR5 ecosystem and keeps the same standard mechanical and electrical interfaces,” he said. “The deployment largely becomes a platform validation exercise rather than a major redesign or hardware swap.”

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Memory continues to be the primary bottleneck in AI and HPC systems, Youssefi said, as bandwidth improvements have not kept the same pace as the growth in compute capability. “Memory is becoming the constraint here rather than the compute capability itself.”

The impact of the memory bottleneck is compounded as data centers move from a training-centric AI cycle to the inference era. “These applications come with massive models, massive parameters, and data that require that memory,” Youssefi said.

During inference, latency directly affects the user experience, whether the task is unlocking a device, choosing a driver in a ride-hailing app, or serving real-time enterprise workloads. He said having these services available faster comes with infrastructure requirements. “That infrastructure depends on CPUs, GPUs, compute engines, machine learning models, and deep learning models that support inference.”

The transition to more inference-heavy AI comes at a time when performance per watt is a critical metric for data centers, which Youssefi said is another selling point of Renesas’ MRDIMM chipsets.

MRDIMM improves performance per watt by delivering much higher memory bandwidth with lower latency without requiring DRAM chips to run at higher speeds, he said. Because the DRAM does not have to be overclocked, the system can do more useful work at roughly the same memory power, Youssefi said.

Renesas’ release echoes that emphasis, saying Gen 3 was designed with system-level power efficiency in mind as customers balance higher bandwidth against thermal and power constraints. For semiconductor engineers, that combination of higher bandwidth and controlled power draw is likely the key design point, especially in AI servers where memory is often the limiting subsystem.

Renesas’ Gen 3 DDR5 MRDIMM chipset is a platform, not a single chip pair. Youssefi said the company’s portfolio is uniquely positioned to complete memory interface stack by MRCD, MDB, PMICs, SPD hubs, and temperature sensors.

By allowing the CPU to access two ranks simultaneously, MRCDs effectively double the data rate and throughput compared to traditional RDIMMs. (Source: Renesas)

Renesas is not the only company tackling the memory bottleneck with DIMM technology. Rambus recently announced its DDR5 9600 Server RDIMM chipset built around its new Rambus 6th Generation Registering Clock Driver (RCD06). The chipset is claimed to deliver a 20% increase in bandwidth over the previous generation, enabling RDIMMs operating at up to 9,600 MT/s.

Like Renesas, Rambus is looking to improve bandwidth and capacity to support agentic AI, HPC, and other data-intensive workloads.

Youssefi said this kind of incremental but architectural bandwidth gain may prove more valuable than a wholesale platform redesign if AI and HPC demand continues to rise as expected. “Memory bandwidth has become one of the most important constraints in AI, HPC, and cloud computing environments.”