AI Compute Infrastructure Directory

Comprehensive dataset of computing platforms, hardware, and infrastructure for AI workloads

AI Compute Infrastructure Directory Dataset

Discover the complete ecosystem of compute infrastructure solutions powering modern AI and machine learning applications. From GPU cloud providers to specialized AI chips, this directory covers everything you need to build scalable, high-performance AI computing infrastructure.

GPU Cloud Providers

GPU cloud computing, AI training infrastructure, machine learning GPU rental, high-performance computing

Company/Product	Category	Description	Key Features	GPU Types	Pricing Model
NVIDIA DGX Cloud	Enterprise GPU	NVIDIA's dedicated AI computing platform	DGX systems, optimized for AI, enterprise support	H100, A100, V100	Monthly/Annual
AWS EC2 GPU Instances	Cloud GPU	Amazon's elastic GPU compute instances	P4, P3, G4 instances, spot pricing, auto-scaling	A100, V100, T4, K80	On-demand/Reserved
Google Cloud GPU	Cloud Computing	Google's GPU-accelerated compute platform	Preemptible instances, TPU integration, custom VMs	A100, V100, T4, K80	Pay-as-you-go
Microsoft Azure GPU	Cloud Platform	Azure's GPU compute solutions	NC, ND, NV series, HPC clusters	H100, A100, V100, M60	Consumption-based
Lambda Labs	GPU Cloud	Specialized GPU cloud for ML training	On-demand GPUs, Jupyter notebooks, PyTorch pre-installed	A100, RTX 6000, GTX 1080 Ti	Hourly/Monthly

Specialized AI Chips & Hardware

AI accelerators, neural processing units, edge AI chips, custom AI hardware

Company/Product	Category	Description	Key Features	Use Cases	Target Market
Google TPU	Tensor Processing Unit	Google's custom AI accelerator	Matrix operations, TensorFlow optimization, cloud/edge	Large-scale ML training, inference	Cloud/Enterprise
NVIDIA H100	GPU Accelerator	Latest generation data center GPU	Transformer engine, multi-instance GPU, NVLink	LLM training, generative AI, HPC	Data centers
Intel Habana Gaudi	AI Training Processor	Intel's AI training accelerator	High memory bandwidth, scalable architecture	Deep learning training, research	Enterprise/Cloud
Cerebras CS-2	Wafer-Scale Engine	World's largest AI processor	850,000 cores, 40GB on-chip memory	Large model training, research	Supercomputing
Graphcore IPU	Intelligence Processing Unit	Processor designed for AI workloads	Massive parallelism, low-latency memory	Graph neural networks, research	AI research/Enterprise

Edge AI Computing

Edge AI hardware, mobile AI chips, IoT processors, embedded AI computing

Company/Product	Category	Description	Key Features	Use Cases	Form Factor
NVIDIA Jetson	Edge AI Platform	Complete AI computing platform for edge	GPU acceleration, compact design, developer tools	Robotics, autonomous machines, IoT	System-on-Module
Intel Neural Compute Stick	USB AI Accelerator	Plug-and-play deep learning inference	OpenVINO toolkit, low power, portable	Prototyping, edge inference	USB stick
Google Coral	Edge AI	Google's edge AI development platform	Edge TPU, TensorFlow Lite, camera modules	Smart cameras, industrial IoT	Dev boards/modules
Qualcomm AI Engine	Mobile AI	AI acceleration for mobile devices	Hexagon DSP, Adreno GPU, Kryo CPU	Smartphones, automotive, XR	Mobile SoCs
Apple Neural Engine	Mobile AI Chip	Apple's dedicated neural processing unit	On-device ML, privacy-focused, low power	iPhone, iPad, Mac AI features	Integrated SoC

High-Performance Computing (HPC)

AI supercomputing, distributed training infrastructure, HPC clusters, parallel computing

Company/Product	Category	Description	Key Features	Use Cases	Scale
NVIDIA DGX SuperPOD	AI Supercomputer	Turnkey AI infrastructure solution	InfiniBand networking, optimized software stack	Large-scale AI research, enterprise	Petascale
IBM Power Systems	HPC Platform	IBM's AI-optimized server platform	POWER processors, GPU acceleration, high bandwidth	AI training, scientific computing	Enterprise
HPE Apollo	HPC Systems	HPE's high-density compute solutions	Liquid cooling, GPU density, fabric options	Research institutions, cloud providers	Rack-scale
Dell EMC PowerEdge	Server Platform	Dell's AI-ready server portfolio	GPU support, scalable architecture, management tools	Enterprise AI, data centers	Server/Cluster
Lenovo ThinkSystem	AI Infrastructure	Lenovo's AI-optimized server solutions	Neptune liquid cooling, GPU configurations	Research, enterprise AI	Data center

Container & Orchestration Platforms

Kubernetes for AI, container orchestration, ML workload management, cloud-native AI

Company/Product	Category	Description	Key Features	Use Cases	Deployment
Kubernetes	Container Orchestration	Open-source container orchestration platform	Auto-scaling, load balancing, service discovery	ML model serving, training jobs	Multi-cloud
Kubeflow	ML Orchestration	ML workflows on Kubernetes	Pipelines, training operators, model serving	End-to-end ML workflows	Kubernetes
Amazon EKS	Managed Kubernetes	AWS managed Kubernetes service	GPU node groups, spot instances, auto-scaling	ML training, inference serving	AWS
Google GKE	Managed Kubernetes	Google's managed Kubernetes platform	TPU integration, Autopilot mode, AI/ML optimized	ML workloads, batch processing	Google Cloud
Red Hat OpenShift	Enterprise Kubernetes	Enterprise Kubernetes platform	Developer tools, security, hybrid cloud	Enterprise ML, DevOps	Hybrid/Multi-cloud

Specialized Infrastructure Solutions

AI Training Infrastructure

Tools: Run:ai, Determined AI, Weights & Biases, Neptune, Polyaxon

Applications: AI model training infrastructure, distributed training platforms, neural network training clusters

Inference Infrastructure

Tools: TensorFlow Serving, NVIDIA Triton, KServe, Seldon Core, BentoML

Applications: AI model serving, inference optimization, real-time ML serving, production AI infrastructure

Distributed Computing Frameworks

Apache Spark

Unified analytics engine for large-scale data - MLlib, distributed computing, in-memory processing

Ray

Framework for scaling AI and Python applications - Distributed training, hyperparameter tuning, reinforcement learning

Dask

Parallel computing library for Python - DataFrame operations, machine learning, dynamic scheduling

Horovod

Uber's distributed deep learning framework - Multi-GPU/node training, framework agnostic

Cloud Provider AI Accelerators

Amazon Web Services (AWS)

EC2 GPU Instances, AWS Trainium, AWS Inferentia, SageMaker, ParallelCluster

Google Cloud Platform (GCP)

Compute Engine GPUs, Tensor Processing Units (TPUs), AI Platform, Vertex AI, Google Kubernetes Engine

Microsoft Azure

Virtual Machines, Azure Machine Learning, Azure Batch AI, Azure Kubernetes Service, Azure HPC

Emerging Technologies

Quantum-Classical Hybrid

IBM Quantum Network, Google Quantum AI, Microsoft Azure Quantum, Amazon Braket

Neuromorphic Computing

Intel Loihi, IBM TrueNorth, BrainChip Akida, SpiNNaker

Optical Computing

Lightmatter, Xanadu, LightOn, Luminous Computing

Key Topics & Technologies

Core Technologies

AI compute infrastructure, GPU cloud computing, machine learning hardware, AI training infrastructure, edge computing platforms

Advanced Solutions

Distributed computing frameworks, AI accelerators, cloud GPU providers, high-performance computing, container orchestration

Best Practices

Best GPU cloud providers 2025, affordable AI training infrastructure, enterprise edge computing solutions, Kubernetes for machine learning, distributed deep learning frameworks