Archive for the 'AI' Category
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September 22, 2026
Is Memory the New Network? Inside the First MemNetAI Workshop at SIGCOMM
By Abed Mohammad Kamaluddin, Director, Custom Cloud Solutions, Marvell, and Vienna Alexander, Marketing Content Professional, Marvell
For most of the last decade, scaling AI meant scaling compute. If you built faster accelerators and wired enough of them together, the models would follow.
That is no longer the whole picture. Models now run to hundreds of billions of parameters with extensive context windows, and whether an expensive accelerator is working or just waiting comes down to memory: how much you have, how fast you can reach it, and how much time you lose moving data around.
Once memory leaves the server and rides a switched fabric, is it still memory, or has it become a network? This was the central question of MemNetAI, the first workshop on Memory-Semantic Networking for AI-Scale Systems, launched by Marvell with researchers from IIT Hyderabad and IIIT Delhi. Held at ACM SIGCOMM 2026 in Denver and guided by a program committee spanning academia and industry, it brought speakers from Cornell, alongside industry experts and researchers presenting their work, to debate these questions on the bleeding edge of AI infrastructure.
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September 15, 2026
Breaking Through the KV Cache Memory Wall with DPU-powered Network Storage
By Chander Chadha, Director of Product Marketing, Storage Products, Marvell
As AI models grow larger and inference workloads scale, larger models, longer context windows and growing KV caches are driving demands on memory resources. Traditional CPU-centric networked JBOF (Just Bunch of Flash) can’t keep pace with the throughput, latency, and efficiency requirements of these modern AI clusters.
DPU (data processing unit) -based storage is a compelling alternative to traditional storage, acting as the broker between the network and SSD for remote storage. By offloading storage, networking and security processing from the host CPU onto a dedicated DPU, AI infrastructure can move data closer to compute, reduce latency, and free up valuable CPU cycles for AI workloads.
To address this need, Marvell offers the OCTEON DPU family, purpose-built for hyperscale cloud workloads and data center applications, extending its use specifically into network storage acceleration for AI environments.
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September 10, 2026
Marvell Demonstrates Scalable CXL Memory Infrastructure with Intel
By Khurram Malik, Associate Vice President, Custom Cloud Solutions, Marvell
The rapid growth of AI is creating unprecedented demand for memory capacity. As models get larger and workloads become more data-intensive, traditional server architectures are increasingly challenged to scale memory efficiently.
At Flash Memory Summit (FMS), Marvell demonstrated how CXL can enable a more flexible and scalable approach to memory infrastructure, showcasing an end-to-end architecture at the Intel® booth.
The demonstration combined an Intel platform with three Marvell® technologies: Structera® X CXL memory expander, Structera® S CXL switch and Alaska® P PCIe retimer. Together, they demonstrated how memory expansion, CXL switching and high-speed PCIe connectivity can work together within a real server platform.
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September 09, 2026
Marvell Structera X Extends CXL Interoperability to NVIDIA Vera
By Arifur Rahman, Director of Product Marketing, Custom Cloud Solutions, Marvell
Memory has become the defining constraint of modern AI infrastructure. Large language models, in-memory databases, and deep learning recommendation models all share the same bottleneck: there is never enough DRAM. Compute Express Link (CXL) was designed to break that bottleneck but a CXL memory expander is only as valuable as the breadth of platforms it can run on.
That is why ecosystem enablement is a core pillar of Marvell's CXL strategy. Today we are marking a new milestone: successful interoperability of the Marvell® Structera™ X CXL memory-expansion controller with the NVIDIA Vera CPU platform.
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August 20, 2026
Shedding Light on AI's Blindspot
By Uniquely Wired, Profile of Angelina Totović, Principal Engineer, Photonic Fabric Business Unit, Marvell
This article was originally published in Uniquely Wired.
The frontier of photonics is among the least predictable corners of modern engineering, a place where quiet research can grow into $5.5 billion dollar acquisitions inside a five-year window, and where the engineers closest to the science are often so invested in the technological developments that they are the last to learn how much value they have actually created. Angelina has been inside that turbulence from the start. The deal Marvell struck with Celestial AI in late 2025, the largest event in her professional life so far, arrived through her newsfeed the same way it arrived for everyone else. The role she holds today did not exist when she first sat down to work on the technology that produced it. Read across the whole arc, her career has been one long exercise in learning to work with things she could not predict.
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