NVIDIA has reportedly discontinued its dual-rack GB200 NVL36x2 GPU model, opting to focus on the single-rack GB200 NVL72 and NVL36 models. This shift, revealed by industry analyst Ming-Chi Kuo, aims to simplify NVIDIA's offerings in the AI and HPC markets. The decision was influenced by major clients like Microsoft, who prefer the NVL72's improved space efficiency and potential for enhanced inference performance. While both models perform similarly in AI large language model (LLM) training, the NVL72 is expected to excel in non-parallelizable inference tasks. As a reminder, the NVL72 features 36 Grace CPUs, delivering 2,592 Arm Neoverse V2 cores with 17 TB LPDDR5X memory with 18.4 TB/s aggregate bandwidth. Additionally, it includes 72 Blackwell GB200 SXM GPUs that have a massive 13.5 TB of HBM3e combined, running at 576 TB/s aggregate bandwidth.

However, this shift presents significant challenges. The NVL72's power consumption of around 120kW far exceeds typical data center capabilities, potentially limiting its immediate widespread adoption. The discontinuation of the NVL36x2 has also sparked concerns about NVIDIA's execution capabilities and may disrupt the supply chain for assembly and cooling solutions. Despite these hurdles, industry experts view this as a pragmatic approach to product planning in the dynamic AI landscape. While some customers may be disappointed by the dual-rack model's cancellation, NVIDIA's long-term outlook in the AI technology market remains strong. The company continues to work with clients and listen to their needs, to position itself as a leader in high-performance computing solutions.

Marvell Technology, Inc., a leader in data infrastructure semiconductor solutions, today launched the Marvell Structera product line of Compute Express Link (CXL) devices that enable cloud data center operators to overcome memory performance and scaling challenges in general-purpose servers.

To address memory-intensive applications, data center operators add extra servers to get higher memory bandwidth and higher memory capacity. The compute capabilities from the added processors are typically not utilized for these applications, making the servers inefficient from cost and power perspectives. The CXL industry standard addresses this challenge by enabling new architectures that can efficiently add memory to general-purpose servers.

Google has officially joined the club of custom Arm-based, in-house-developed CPUs. As of today, Google's in-house semiconductor development team has launched the "Axion" CPU based on Arm instruction set architecture. Using the Arm Neoverse V2 cores, Google claims that the Axion CPU outperforms general-purpose Arm chips by 30% and Intel's processors by a staggering 50% in terms of performance. This custom silicon will fuel various Google Cloud offerings, including Compute Engine, Kubernetes Engine, Dataproc, Dataflow, and Cloud Batch. The Axion CPU, designed from the ground up, will initially support Google's AI-driven services like YouTube ads and Google Earth Engine. According to Mark Lohmeyer, Google Cloud's VP and GM of compute and machine learning infrastructure, Axion will soon be available to cloud customers, enabling them to leverage its performance without overhauling their existing applications.

Google's foray into custom silicon aligns with the strategies of its cloud rivals, Microsoft and Amazon. Microsoft recently unveiled its own AI chip for training large language models and an Arm-based CPU called Cobalt 100 for cloud and AI workloads. Amazon, on the other hand, has been offering Arm-based servers through its custom Graviton CPUs for several years. While Google won't sell these chips directly to customers, it plans to make them available through its cloud services, enabling businesses to rent and leverage their capabilities. As Amin Vahdat, the executive overseeing Google's in-house chip operations, stated, "Becoming a great hardware company is very different from becoming a great cloud company or a great organizer of the world's information."

Synopsys today announced it has expanded its collaboration with Arm to provide optimized IP and EDA solutions for the newest Arm technology, including the Arm Neoverse V2 platform and Arm Neoverse Compute Subsystem (CSS). Synopsys has joined Arm Total Design where Synopsys will leverage their deep design expertise, the Synopsys.ai full-stack AI-driven EDA suite, and Synopsys Interface, Security, and Silicon Lifecycle Management IP to help mutual customers speed development of their Arm-based CSS solutions. The expanded partnership builds on three decades of collaboration to enable mutual customers to quickly develop specialized silicon at lower cost, with less risk and faster time to market.

"With Arm Total Design, our aim is to enable rapid innovation on Arm Neoverse CSS and engage critical ecosystem expertise at every stage of SoC development," said Mohamed Awad, senior vice president and general manager, Infrastructure Line of Business at Arm. "Our deep technical collaboration with Synopsys to deliver pre-integrated and validated IP and EDA tools will help our mutual customers address the industry's most complex computing challenges with specialized compute."

The United States has recently imposed several sanctions on technology exports to China. These sanctions are designed to restrict the transfer of specific technologies and sensitive information to Chinese entities, particularly those with ties to the Chinese military or government. The primary motivation behind these sanctions is to protect American national security interests, as well as to protect American companies from unfair competition. According to Financial Times, we have information that Chinese tech Giant, Alibaba, can not access Arm licenses for Neoverse V1 technology. Generally, the technology group where Neoverse V-series falls in is called Wassenaar -- multilateral export control regime (MECR) with 42 participating states. This agreement prohibits the sale of technology that could be used for military purposes.

The US argues that Arm's Neoverse V1 IP is not only a product from UK's Arm but a design made in the US as well, meaning that it is a US technology. Since Alibaba's T-Head group responsible for designing processors that go into Alibaba's cloud services can not use Neoverse V1, it has to look for alternative solutions. The Neoverse V1 and V2 can not be sold in China, while Neoverse N1 and N2 can. Alibaba's T-Head engineer argued, "We feel that the western world sees us as second-class people. They won't sell good products to us even if we have money."