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Recent news

• Jul 9, 2026

  Pittsburgh Supercomputing Center awarded $10m by NSF for Bridges-3 supercomputer

  The National Science Foundation has awarded the Pittsburgh Supercomputing Center $10 million for Bridges-3, the next generation of its flagship supercomputer.

  • NSF funding: PSC said the award will support Bridges-3, built by HPE with Nvidia B200 GPUs, high-core-count AMD CPU nodes, an all-flash Lustre file system, and Nvidia InfiniBand networking.
  • Timeline and context: Construction is expected to begin at PSC’s new data center in early 2027, with the system slated to come online in the summer of 2027; PSC said it will expand on Bridges-2 and serve a range of scientific workloads including modeling, simulation, data analytics, and AI.
• Jul 9, 2026

  NSF’s $20M Quantum Push: What It Could Mean for Future Data Centers

  The US National Science Foundation (NSF) has announced $20 million in additional funding for five quantum research teams as part of its National Quantum Virtual Laboratory program.

  • NSF selected five additional teams to join the National Quantum Virtual Laboratory, with each team receiving $4 million over two years to refine development plans for fault-tolerant computing, quantum networking, and next-generation sensing.
  • The program expands to nine design projects total, involves researchers across 20 US states and partners including NASA, NIST, Department of Energy national laboratories, and industry participants such as Nvidia, Honeywell, IonQ, and Quantinuum; it also supports the White House executive order on quantum innovation.
• Jul 3, 2026

  Marvell boosts custom silicon push with AMD engineering lead hire

  Marvell Technology has hired former AMD engineering lead Jay Kirkland as SVP of custom silicon engineering.

  • Kirkland joins Marvell after more than six years at AMD, where he led customer engineering, platform engineering, and AI enablement for hyperscale and AI customers.
  • Marvell is also pursuing custom silicon, AI networking, and optical interconnects; the article cites a $2 billion Nvidia investment in Marvell and Marvell’s $3.25 billion acquisition of Celestial AI.
  • The story also mentions Marvell’s Teralynx T100 switch for AI and cloud data center infrastructure, and its acquisitions of Polariton Technologies and Celestial AI.
• Jun 17, 2026

  HPE Discover: Neri outlines an AI architecture built for agents

  HPE announced at HPE Discover 2026 in Las Vegas new AI-focused product and platform updates across networking, compute, storage and cloud.

  • Main announcement: HPE detailed cross-portfolio AI updates including new networking hardware (QFX switches, PTX 12,000 with 800G routing, SRX 4700 quantum-safe firewall at 1.44 Tbps, MX 301 edge router), compute (ProLiant DL 394 Gen 12; Private Cloud AI scaling to 256 GPUs with multi-node inference and a three-tier AI Factory), storage (Alletra MPX 10,000 as the Private Cloud AI storage layer with native MCP and Nvidia Certified Storage validation), and cloud/management (HPE CloudOps consolidation and Unleash AI program covering 60+ validated partners).
  • Background and specifics: Announcements include agentic governance (zero-code agent registration, three-tier identity model, Nvidia Open Shell, NeMo Cloud workflows, Zerto rollback), performance claims (AI training with one-quarter the GPUs vs prior Blackwell-generation platform; inference at one-tenth the cost per million tokens; 7 to 12x faster time to value vs custom environments), and an energy warning citing a projected 19 gigawatt U.S. power gap by 2028 and data centers accounting for nearly half of U.S. electricity demand through 2031.
• May 29, 2026

  Data Center Hardware Highlights: June 2026

  Blackstone and Google have launched a $5B TPU infrastructure venture.

  • $5B TPU venture: Blackstone and Google announced a $5 billion partnership to build TPU-focused AI infrastructure, signaling a move toward vertically integrated AI compute financed by private capital. The announcement is the central deal highlighted in May’s coverage.
  • Broader May highlights: Data Center Knowledge reports shifts across the stack in May: AI server vendors moving from silicon to services; Nvidia expanding spending beyond GPUs (including networking, cooling, power) and engaging with Iris Energy’s 5 GW pipeline; AMD posted 57% data center growth tied to accelerators; GPU rental pricing shows early compression; battery storage gains traction as diesel alternatives; and geopolitical risk (notably Iran) threatens PCB supply chains.
• May 13, 2026

  AI Server Market Update: Vendors Shift from Silicon to Services

  Data Center Knowledge reports that server vendors are shifting toward software, professional services, and AIOps to win enterprise AI customers.

  • Main announcement: Vendors including Dell, HPE, Lenovo, and Supermicro are emphasizing software management, professional services, AIOps, and liquid-cooling/packaged rack solutions to capture enterprise AI demand; IDC projects AI infrastructure spending to reach $487 billion in 2026 and surpass $1 trillion by 2029, while suppliers report large backlogs (e.g., Dell $43 billion AI backlog, HPE $5 billion AI systems backlog, Lenovo $15.5 billion AI server pipeline).
  • Background & details: The article is an industry analysis citing interviews and earnings: IDC reported the global server market at $444 billion (2025); vendors report specific results such as Dell $9 billion AI-optimized server revenue (Q4 FY2027) and Supermicro $10.2 billion sales (FYQ3 FY2026); it highlights enterprise skill gaps, GPU/memory supply constraints, and differentiation via integration, delivery speed, power & cooling, and services.
• May 1, 2026

  What Next Gen Chips Might Mean for Data Centers

  Data Center Knowledge presents analysis of semiconductor innovations for data centers.

  • Main finding: The article argues that semiconductor-level innovation (AI-optimized chips, energy-optimized and heat-tolerant designs, advanced packaging such as chiplets and 2D/3D, and offload silicon like DPUs/IPUs/SmartNICs) could reshape how data centers are built, powered, cooled, and secured; current adoption is constrained by x86 inertia and software compatibility challenges.
  • Background/details: The piece surveys existing technologies (GPUs, ASICs, FPGAs, ARM-based servers), highlights materials research (graphene, carbon nanotubes) as early-stage, and notes concrete operational benefits including reduced power draw and lower cooling/water use, but it does not announce specific commercial deployments or timelines.
• Apr 9, 2026

  Hyperscalers will own two-thirds of data center capacity by 2031

  Synergy Research Group reported that hyperscalers will account for 67% of all data center capacity by 2031.

  • Main announcement: Synergy Research Group says hyperscalers (Google, Microsoft, AWS) will reach 67% of global data center capacity by 2031, with enterprise on-prem data centers dropping from 56% in 2018 to 19% by 2031; the report also notes almost 60% of hyperscale capacity is in own-built facilities and non-hyperscale colocation accounts for ~20%.
  • Background & details: The article cites planned > $500 billion in capex by Google/Microsoft/AWS for AI infrastructure in fiscal year 2026, cites hyperscalers operating ~1,297 large data centers in Q3 2025 (1,360 by end-2025), references commitments such as the Ratepayer Protection Pledge (Google, Oracle, xAI, Meta, Microsoft, OpenAI, Amazon) and highlights electricity demand concerns (EIA: price hikes up to 79% in areas like Texas by 2027); it references expanded compute partnerships (Anthropic–Google/Broadcom; OpenAI–AMD) with multi-gigawatt capacity starting 2027.
• Apr 7, 2026 · IT Brief Asia

  Nutanix adds AI & cloud tools amid infrastructure push

  Nutanix has announced additions to the Nutanix Cloud Platform including new AI, Kubernetes on bare-metal, expanded storage and cloud management capabilities.

  • Main announcement: Nutanix introduced Agentic AI (early access) and NKP Metal (early access), made Unified Storage 5.3 and Data Lens 2.0generally available, and released Nutanix Cloud Manager 2.0 GA; it also launched a Foundation Central appliance to simplify AHV deployment on servers from Cisco, Dell, Fujitsu, HPE and Lenovo and expanded synchronous DR support for Dell PowerFlex and integration for Everpure //c FlashArray. These features target AI workloads, bare-metal Kubernetes, air-gapped on-prem deployments, and multisite/multidomain cluster management.

  • Background and details: The updates address server and storage supply constraints and aim to broaden deployment options (on-premise, edge, public cloud) including AWS GovCloud support; other planned ecosystem support includes AMD GPU-accelerated servers, Dell PowerStore, NetApp ONTAP, Lenovo ThinkSystem, additional Cisco integrations, zero-copy migrations from VMware vSphere Virtual Volumes to AHV vDisks, and a certified integration between Nutanix Database Service and MongoDB Ops Manager.

• Apr 3, 2026

  ‘Inference Is Bigger Than Any One Chip’ – d-Matrix CEO on GigaIO Deal

  d-Matrix has announced the acquisition of GigaIO’s data center business to internalize interconnect technology and accelerate delivery of rack-scale AI inference infrastructure.

  • Business action: d-Matrix completed a business unit acquisition of GigaIO’s data center assets (ownership of the unit’s related assets transfers to d-Matrix); financial terms were not disclosed; the deal builds on a collaboration that began in 2025 and integrates GigaIO’s SuperNode and FabreX PCIe fabric into d-Matrix’s inference stack (which also includes Corsair inference accelerators, JetStream networking, Aviator software, and the SquadRack reference architecture developed with Broadcom and Arista).
  • Background & implementation details: GigaIO will continue operating independently and refocus on edge computing; a team of systems engineers based in Carlsbad, California joins d-Matrix, establishing a new Southern California engineering presence; d-Matrix now operates six innovation hubs across North America, Europe, and Asia; target customers include hyperscalers, frontier AI labs, and enterprise deployments.
• Apr 2, 2026

  The Genesis Mission: How AI Supercomputing Is About to Reshape American Science and Energy

  The U.S. Department of Energy (DOE) has launched the Genesis Mission, chartered to double U.S. R&D productivity within a decade by deploying a platform combining high-performance computing, AI supercomputing, and quantum computing.

  • Main action: The DOE’s Genesis Mission is standing up national AI supercomputing infrastructure through the Genesis Consortium with 27 industrial partners, including Nvidia, Oracle, AMD, and HPE; Argonne will host a system with ~10,000 GPUs (operational this year), Oak Ridge will host a comparably sized cluster targeting 2026, and a 100,000-GPU cluster is planned for Argonne in 2027. The program pairs this compute platform with a portfolio of national challenges (energy, physical sciences, national security) and a university engagement effort to train future scientists in AI-enabled methods.
  • Background and concrete details: The initiative was launched by President Trump and chartered through the DOE; examples cited include fusion surrogate models that run thousands to tens of thousands times faster than traditional simulations, Grid FM from Brookhaven that could cut a ~20-year grid-simulation workload to two months, and DOE Office of Electricity efforts to reduce interconnection delays by addressing the 80–90% deficiency rate in interconnection applications. Named private partners and startups involved include Periodic Labs, Radical AI, and the Prometheus Project.
• Apr 1, 2026

  OpenAI Raises $122B to Expand AI Infrastructure, Broadens Cloud and Chip Strategy

  OpenAI has announced it raised $122 billion in a funding round valuing the company at $852 billion to expand compute capacity, cloud partnerships, and data center infrastructure.

  • Funding and purpose:$122 billion raised at an $852 billion valuation to support expanded compute capacity, cloud partnerships, and data center expansion; OpenAI also expanded its credit facility to $4.7 billion to provide additional flexibility for capacity investments.
  • Infrastructure and partners: OpenAI is working across Microsoft, Oracle, AWS, CoreWeave, and Google Cloud and using a mix of silicon platforms including Nvidia GPUs, AMD chips, AWS Trainium, Cerebras systems, and custom Broadcom silicon; the platform now processes more than 15 billion tokens per minute, and analysts named include Holger Mueller, Daniel Newman, and Matt Kimball.
• Apr 1, 2026

  With new Marvell deal, Nvidia is chasing the AI control layer

  Nvidia has announced a partnership with Marvell Technology and a $2 billion strategic investment in Marvell.

  • Main announcement: Nvidia and Marvell will integrate Marvell XPUs and scale-up networking with Nvidia NVLink Fusion, enabling customers to build “semi-custom” AI infrastructure that mixes non-Nvidia accelerators with Nvidia GPUs, LPUs, DPUs and Spectrum-X switches; Nvidia is investing $2 billion in Marvell as part of the deal. No specific implementation timeline is provided in the article.
  • Background and additional details: The partnership includes collaboration on 5G/6G AI-RAN (Aerial AI-RAN), advanced optical interconnects and silicon photonics; Nvidia has also announced other ecosystem investments (a combined $4 billion for photonics vendors Coherent and Lumentum and a $5 billion purchase of Intel stock) to expand NVLink-enabled architectures and broader ecosystem alignment.
• Mar 31, 2026

  Nvidia Deepens AI Push With $2B Marvell Deal

  Nvidia announced a partnership and a $2 billion investment in Marvell Technology to integrate Marvell’s custom silicon and interconnects into Nvidia’s NVLink Fusion ecosystem.

  • Partnership details: Nvidia is investing $2 billion and has unveiled a collaboration that pairs Marvell’s custom XPUs, NVLink-compatible scale-up networking, optical DSP and silicon photonics with Nvidia’s NVLink Fusion rack-scale architecture; Nvidia will supply Vera CPU, ConnectX NICs, BlueField DPUs, NVLink interconnect, and Spectrum-X switching platform. The announcement was unveiled today and positions Marvell as a semi-custom AI infrastructure enabler within Nvidia’s ecosystem.
  • Background and scope: The deal emphasizes heterogeneous AI architectures and expands NVLink beyond Nvidia-native silicon (Marvell will add NVLink support to its XPUs); the companies will also collaborate on silicon photonics, optical interconnects, and AI-RAN telecom deployments using Nvidia’s Aerial platform. No explicit multi-year timeline or implementation dates were provided in the article.