high performance compute servers

Cloud‑resident high performance compute servers used by hyperscale cloud providers like Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure, Oracle Cloud Infrastructure (OCI), Meta, and others use a mix of custom in‑house designs and ODM (Original Design Manufacturer) ‑ built hardware.

In‑House Design Teams:

Amazon (AWS) – Designs its own Nitro System–based servers, including custom motherboards, networking cards, and security chips. AWS also develops Graviton (Arm‑based) and Trainium/Inferentia (AI) processors. HPC instances use Elastic Fabric Adapter (EFA) for low‑latency interconnects.
Google (GCP) – Builds custom server boards and racks for its data centers, plus TPUs (Tensor Processing Units) for AI workloads. GCP builds custom HPC server boards and racks, plus TPUs for AI workloads. It uses high‑speed interconnects like Google’s Jupiter network for HPC clusters.
Microsoft Azure – Designs Azure‑optimized servers and AI accelerators, often in collaboration with partners, and contributes designs to the Open Compute Project (OCP). It integrates InfiniBand and/or 400 Gbps Ethernet for HPC interconnects.
Oracle – Designs bare‑metal HPC shapes with AMD EPYC, Intel Xeon, and NVIDIA GPUs, plus RDMA cluster networking for microsecond latency.
Meta – Designs its compute servers, especially for AI workloads, by working closely with ODM partners like Quanta Computer, Wiwynn, and Foxconn.

Manufacturing Partners (ODMs/OEMs):

While the hyperscaler compute server designs are proprietary, the physical manufacturing is typically outsourced to Original Design Manufacturers (ODMs) who specialize in hyperscale data center gear as per these tables:

ODM / OEM	Known for	Cloud Customers
Quanta Cloud Technology (QCT)	Custom rack servers, HPC nodes	AWS, Azure, Oracle
WiWynn	OCP‑compliant HPC servers	Microsoft, Meta
Inventec	HPC and AI‑optimized servers	AWS, GCP
Foxconn / Hon Hai	Large‑scale server manufacturing	Google, AWS
Celestica	HPC and networking gear	Multiple hyperscalers
Supermicro	GPU‑dense HPC systems	AWS, Oracle, Azure

ODM / OEM	Role in Hyperscale Cloud
Quanta Cloud Technology (QCT)	Major supplier for AWS, Azure, and others; builds custom rack servers and storage nodes.
WiWynn	Spun off from Wistron; manufactures OCP‑compliant servers for Microsoft and Facebook/Meta.
Inventec	Supplies compute and storage servers for AWS and other CSPs.
Foxconn / Hon Hai	Builds cloud server hardware for multiple providers, including Google.
Delta / Celestica	Provides specialized server and networking gear for hyperscale data centers.
Supermicro	Supplies both standard and custom AI‑optimized servers to cloud and enterprise customers.

The global server market expected to reach $380 billion by 2028. Image credit: Alamy

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Here’s a supply chain relationship map for cloud‑resident high‑performance compute (HPC) servers used by the major hyperscalers:

Hyperscale HPC Server Design & Manufacturing Landscape:

Cloud Provider	In‑House Design Focus	Key Manufacturing / ODM Partners	Notable HPC Hardware Features
Amazon Web Services (AWS)	Custom Nitro boards, Graviton CPUs, Trainium/Inferentia AI chips, EFA networking	Quanta Cloud Technology (QCT), Inventec, Foxconn	Arm‑based HPC nodes, GPU clusters (NVIDIA H100/A100), ultra‑low‑latency RDMA
Google Cloud Platform (GCP)	Custom server boards, TPU accelerators, Jupiter network fabric	Quanta, Inventec, Foxconn	TPU pods, GPU supernodes, liquid‑cooled racks
Microsoft Azure	OCP‑compliant HPC designs, Maia AI chip, Cobalt CPU, InfiniBand networking	WiWynn, QCT, Celestica	Cray‑based HPC clusters, GPU/FPGA acceleration
Oracle Cloud Infrastructure (OCI)	Bare‑metal HPC shapes, RDMA cluster networking	QCT, Supermicro	AMD EPYC/Intel Xeon nodes, NVIDIA GPU dense racks
Meta (for AI/HPC research)	OCP‑based AI/HPC servers	WiWynn, QCT	AI Research SuperCluster, liquid cooling
Alibaba Cloud / Tencent Cloud	Custom AI/HPC boards, Arm CPUs	Inspur, Sugon, QCT	GPU/FPGA acceleration, high‑bandwidth fabrics

Meta’s ODM Collaboration Model:

Quanta Computer: Meta has partnered with Quanta for final assembly of its next-gen AI servers. Quanta is responsible for building up to 6,000 racks of the Santa Barbara servers, which feature advanced cooling and power delivery systems.
Wiwynn & Foxconn: These ODMs also play key roles in Meta’s infrastructure. Wiwynn reportedly earns more than half its revenue from Meta, while Foxconn handles system assembly for NVIDIA’s NVL 72 servers, which Meta may also utilize.
Broadcom Partnership: For chip supply, Meta collaborates with Broadcom to integrate custom ASICs into its server designs.

Hyperscaler/ODM Collaboration Process:

Design Phase – Hyperscalers’ hardware teams define the architecture: CPU/GPU choice, interconnect, cooling, power density.
ODM Manufacturing – Partners like Quanta, WiWynn, Inventec, Foxconn, Celestica, and Supermicro build the servers to spec.
Integration & Deployment – Systems are tested, integrated into racks, and deployed in hyperscale data centers.
Optimization – Providers fine‑tune firmware, drivers, and orchestration for HPC workloads (e.g., CFD, genomics, AI training).

Industry Trends:

Open Compute Project (OCP) – Many designs are shared in the OCP community, allowing ODMs to build interoperable, cost‑optimized hardware at scale. Open Compute Project designs speed up deployment and interoperability.
Vertical Integration – Hyperscalers increasingly design custom silicon (e.g., AWS Graviton, Google TPU, Microsoft Maia AI chip) to optimize performance and reduce dependency on third‑party CPUs/GPUs.
AI‑Optimized Racks – New designs focus on high‑density GPU clusters, liquid cooling, and ultra‑low‑latency networking for AI workloads.
Vertical integration: More custom silicon to optimize performance and cost. See Specialized HPC components below.
Liquid cooling: Increasingly common for dense GPU/CPU HPC racks.

Specialized HPC Components:

CPUs – AMD EPYC, Intel Xeon Scalable, AWS Graviton (Arm), custom Google CPUs.
GPUs / Accelerators – NVIDIA H100/A100, AMD Instinct, Google TPU, AWS Trainium.
Networking – Mellanox/NVIDIA InfiniBand, AWS EFA, Oracle RDMA cluster networking.
Storage – Parallel file systems like Lustre, BeeGFS, IBM Spectrum Scale for HPC workloads