By Vienna Alexander, Marketing Content Professional, Marvell
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The semiconductor industry is an exciting place to build a career, especially with the exponential growth and demand for hardware innovation in the age of AI—the global semi market is approaching the $1 trillion mark, with 2027’s total market forecast at $831.5 million.1 For young engineers and talent, it provides an opportunity to solve complex problems and work on cutting-edge technology.
By Vienna Alexander, Marketing Content Professional, Marvell
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Marvell was named to both U.S. News’ Best Companies to Work For and TIME’s list of America’s Best Companies for 2026.
By Vikram Dattatri, Senior Engineer, Cloud Platform Group, Marvell
Packet trimming doesn’t prevent traffic losses from occurring; instead, it streamlines the process for recovering them. It is also one of many technologies Marvell is developing to optimize networks for the AI era.
Artificial intelligence infrastructure is driving a fundamental shift in how data center networks are designed, validated, and deployed. As clusters scale to thousands—or even tens of thousands—of GPUs, the network is no longer just a connectivity layer. It becomes a tightly coupled component of the compute system, directly impacting job completion time, efficiency and overall cost.
To address these evolving requirements, Ethernet is undergoing a transformation. At OFC 2026, Marvell and Keysight Technologies demonstrated (see the video below) how next-generation Ethernet fabrics can meet the demands of AI workloads through a combination of advanced features and realistic validation. Leveraging Keysight’s KAI Data Center Builder and AresONE‑M 800GE platform, the collaboration showcased how the Marvell® Teralynx® switch fabric supports emerging Ultra Ethernet Consortium (UEC) capabilities, with a particular focus on packet trimming, Auto Load Balancing (ALB) and Ultra Ethernet Transport (UET).
By Vienna Alexander, Marketing Content Professional, Marvell

TIME Magazine has recognized Marvell as one of the World's Most Sustainable Companies for the third year in a row. Marvell is honored to have been represented since the origin of this ranking, as the company has demonstrated consistent, measurable progress across a number of sustainability initiatives.
By Arifur Rahman, Director of Product Marketing, Custom Cloud Solutions, Marvell
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Modern AI workloads are insatiable consumers of memory. Deep learning recommendation models (DLRM), large language model (LLM) inference, in-memory databases and vector search engines all share a common bottleneck: there is never enough DRAM, and what exists is very expensive.
At today's spot prices—$27–$37 per GB for server-grade DDR5 RDIMMs1—a 12TB memory pool requires nearly half a million dollars in DRAM alone. Meanwhile, AI infrastructure buildouts are consuming server DRAM capacity faster than fabs can produce it, driving prices up 300–400% since mid-2025.1, 2
CXL memory expansion was supposed to solve this. And it does—but there's a subtler lever that most solutions ignore: the data sitting in that memory is compressible, and most CXL controllers don't touch it.
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