Research Notes
Research Note: Marvell Custom HBM for Cloud AI
Marvell recently announced a new custom high-bandwidth memory (HBM) compute architecture that addresses the scaling challenges of XPUs in AI workloads. The new architecture enables higher compute and memory density, reduced power consumption, and lower TCO for custom XPUs.
Research Note: Enfabrica ACF-S Millennium
First detailed at Hot Chips 2024, Enbrica recently announced that its ACF-S “Millennium” chip, which addresses the limitations of traditional networking hardware for AI and accelerated computing workloads, will be available to customers in calendar Q1 2025.
Research Note: Cohesity & Veritas Complete Merger
Cohesity completed its long-awaited merger with Veritas’ enterprise data protection business. The combined entity, valued at $7 billion, now serves 12,000 customers globally and generates $1.5 billion in ARR.
Research Note: Dell AI Products & Services Updates
Dell Technologies has made significant additions to its AI portfolio with its recent announcements at SC24 and Microsoft Ignite 2024 in November. The announcements span infrastructure, ecosystem partnerships, and professional services, targeting accelerated AI adoption, operational efficiency, and sustainability in enterprise environments.
Research Note: AWS Trainium2
Tranium is AWS’s machine learning accelerator, and this week at its re:Invent event in Las Vegas, it announced the second generation, the cleverly named Trainium2, purpose-built to enhance the training of large-scale AI models, including foundation models and large language models.
Research Note: Hammerspace Global Data Platform v5.1 with Tier 0
Hammerspace recently announced the version 5.1 release of its Hammerspace Global Data Platform. The flagship feature of the release its new Tier 0 storage capability, which takes unused local NVMe storage on a GPU server and uses it as part of the global shared filesystem. This provides higher-performance storage for the GPU server than can be delivered from remote storage nodes – ideal for AI and GPU-centric workloads.