Marvell Blogs

Marvell Newsroom

Latest Marvell Blog Articles

  • August 05, 2026

    Marvell® Photonic Fabric™ Wins AI Infrastructure Award at FMS 2026

    By Vienna Alexander, Marketing Content Professional, Marvell

    At the Future of Memory and Storage (FMS) trade show, Marvell won the AI Infrastructure award for its Photonic Fabric™ technology, a transformational optical interconnect platform that overcomes the bandwidth and memory bottlenecks limiting AI infrastructure. By replacing electrical interconnects with optical I/O across package-, server- and rack-scale architectures, Marvell® Photonic Fabric™ enables scalable AI systems with dramatically higher bandwidth, lower latency, reduced power consumption and unprecedented memory scalability.

    Memory bandwidth, memory locality and data movement are pressing constraints on AI training and inference scalability and token efficiency. Traditional architectures were not designed to support hundreds or thousands of accelerators across multiple racks. Photonic Fabric technology facilitates a new generation of disaggregated memory architectures where memory capacity is no longer constrained by the physical boundaries of individual servers or packages.

  • August 05, 2026

    Accelerating AI Infrastructure with Marvell Structera A and SK hynix CXL Memory: Enabling Efficient Near-Memory Processing

    By Khurram Malik, Associate Vice President, Custom Cloud Solutions, Marvell, and Kangkyu Park, Vice President, System Architecture, SK hynix

    The rapid growth of AI workloads is creating unprecedented demands on data center architectures. Modern AI applications, including large language models (LLMs), generative AI, recommendation systems, and high-performance computing, require significantly higher memory capacity, bandwidth, and efficiency.

    Traditional compute-centric architectures are increasingly limited by the movement of data between processors and memory. As AI models continue to scale, excessive data movement creates performance bottlenecks, increases latency, and drives higher power consumption.

    To address these challenges, the industry is moving toward memory-centric computing architectures enabled by Compute Express Link® (CXL®). CXL enables flexible memory expansion, memory pooling, and new system architectures that allow compute resources to operate more efficiently.

    Marvell and SK hynix are collaborating to enable the next generation of memory-centric computing by combining Marvell® Structera™ A CXL-based near-memory acceleration technology with SK hynix advanced memory solutions. Together, Marvell and SK hynix are helping accelerate the adoption of CXL-enabled architectures for AI data centers by delivering a highly efficient and scalable approach to memory processing.

  • August 04, 2026

    Marvell Structera™ X, A and S: A Comprehensive CXL Portfolio Powering AI Memory Innovation

    By Khurram Malik, AVP, Data Center Memory and Storage Solutions, Marvell

    CXL has become one of the most important technologies shaping AI infrastructure. As hyperscalers race to deploy larger AI models, longer context windows and increasingly memory-intensive inference workloads, memory capacity and bandwidth have emerged as critical constraints on performance, efficiency and scaling. At the same time, CXL adoption is reaching an inflection point, moving from evaluation into real-world deployment across hyperscale environments.

    Marvell is leading this transition with Structera™ X memory expansion solutions developed alongside the world’s leading hyperscalers. The story begins with the shipping of Structera X 2404 and 2504 platforms, which have enabled hyperscalers to expand memory resources more efficiently, including extending the useful life of existing DDR4 investments while powering demanding AI workloads.

    Structera X is not a series of disconnected product eras—it is a single, continuous architectural evolution. Today’s generation is already delivering real hyperscaler deployments, ecosystem maturity and a compelling TCO advantage. From that foundation, Marvell is extending the architecture toward the next phase of AI infrastructure innovation, adding capabilities enabled by the evolving CXL 3.2 ecosystem, PCIe Gen 6 connectivity and more advanced multi-host memory sharing architectures. These advancements will create larger, more flexible memory pools, enabling more efficient sharing of resources across servers and improving infrastructure utilization at hyperscale. As the architecture advances, Marvell is driving it toward higher bandwidth, deeper data optimization and increasingly disaggregated memory environments built to meet the growing demands of AI workloads.

  • August 04, 2026

    Photonic Fabric™ Technology: How Optical Connectivity Enables the Next Generation of AI Infrastructure

    By Ravi Mahatme, Senior Director, Product Management, Photonic Fabric Business Unit, Marvell

    AI infrastructure is entering a new architectural era. As AI inference scales, performance increasingly depends not simply on adding more compute, but on how efficiently compute, memory and connectivity operate together as one unified AI infrastructure system. Modern AI inference workloads are insatiable consumers of memory. Large language models, reasoning models and agentic AI applications require rapid access to model parameters, embeddings and rapidly growing key-value (KV) caches that preserve conversational context. These working data sets are growing into the hundreds of gigabytes, and increasingly terabytes, making memory capacity, bandwidth and latency just as important as accelerator performance. As AI infrastructure scales, overall system performance increasingly depends on how efficiently accelerators can access, move and utilize memory resources rather than simply adding more compute.

    Why AI Needs a New Memory Tier

    Today's AI memory hierarchy was never designed for inference at the scale modern workloads demand. High bandwidth memory (HBM) attached directly to GPUs delivers exceptional performance but remains expensive and capacity constrained. System DRAM provides larger memory pools but cannot economically scale alongside every accelerator. NVMe SSDs offer abundant capacity, yet their latency makes them unsuitable for serving active inference workloads.

    This challenge is especially visible in large language models, where growing KV caches must remain readily accessible to avoid repeatedly recomputing previous tokens. Keeping these caches entirely in HBM is prohibitively expensive, while moving them to storage introduces latency that reduces token generation performance. The result is that GPUs increasingly spend valuable cycles waiting for data rather than performing inference.

  • August 04, 2026

    Powering the Next Generation of PCIe Gen6 NVMe SSDs with the Marvell® Bravera™ SC6 SSD Controller

    By RC Camillo, Product Management Director, Custom Cloud Solutions, Marvell

    As PCIe Gen6 storage becomes increasingly important for AI infrastructure, cloud platforms, enterprise databases, and hyperscale data centers, SSD controllers must deliver significantly more than raw bandwidth. They need intelligent flash management, enterprise-grade security, advanced error correction and scalable architecture.

    The Marvell® Bravera™ SC6 SSD Controller (MV-SF1410) addresses these challenges by combining PCIe Gen6 connectivity, NVMe 2.2 compliance, support for high-speed NAND flash, powerful multi-core processing, integrated security and advanced reliability technologies into a single enterprise-ready platform. The Marvell® Bravera™ SC6 SSD Controller (MV-SF1410) is engineered to meet the demanding requirements of modern data centers and enterprise storage environments. Designed to support PCIe Gen6 NVMe SSDs, this advanced controller combines exceptional performance, scalability, robust security and intelligent flash management.

Archives