HPC-AI vs. Ray Comparison


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About HPC-AI is an enterprise AI infrastructure and GPU cloud platform designed to accelerate deep learning training, inference, and large-scale compute workloads with high performance and cost efficiency. It delivers a pre-configured AI-optimized stack that enables rapid deployment and real-time inference while supporting demanding workloads that require high IOPS, ultra-low latency, and massive throughput. It provides a robust GPU cloud environment built for artificial intelligence, high-performance computing, and other compute-intensive applications, giving teams the tools needed to run complex workflows efficiently. At its core, the company’s software focuses on parallel and distributed training, inference, and fine-tuning of large neural networks, helping organizations reduce infrastructure costs while maintaining performance. It is powered in part by technologies such as Colossal-AI, which significantly accelerates model training and improves productivity.	About Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience AI developers, researchers, and enterprises that need scalable GPU infrastructure to train and run large machine learning models efficiently	Audience ML and AI Engineers, Software Developers
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing $3.05 per hour Free Version Not Supported Free Trial Not Supported	Pricing Free Open source. Consumption-based. Free Version Supported Free Trial Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Supported Live Online Supported In Person Supported
Company Information HPC-AI Singapore www.hpc-ai.com	Company Information Anyscale Founded: 2019 United States ray.io
Alternatives Compute with Hivenet Hivenet	Alternatives Anyscale
Fluidstack	Horovod
Together AI	Determined AI
Intel Tiber AI Cloud Intel	Neuralhub
IONOS Cloud GPU Servers IONOS View All	Automaton AI View All
Categories AI Cloud Providers Supported AI Fine-Tuning Supported AI Infrastructure Supported Cloud GPU Supported	Categories Deep Learning Supported Machine Learning Supported ML Model Deployment Supported

Integrations Kubernetes Supported PyTorch Supported TensorFlow Supported Amazon EC2 Trn2 Instances Not Supported Amazon EKS Not Supported Amazon SageMaker Not Supported Amazon Web Services (AWS) Not Supported Anyscale Not Supported Apache Airflow Not Supported Azure Kubernetes Service (AKS) Not Supported Dask Not Supported Databricks Not Supported Docker Supported Feast Not Supported Google Kubernetes Engine (GKE) Not Supported Hugging Face Supported LanceDB Not Supported Python Not Supported Union Cloud Not Supported io.net Not Supported Show More Integrations View All 5 Integrations	Integrations Kubernetes Supported PyTorch Supported TensorFlow Supported Amazon EC2 Trn2 Instances Supported Amazon EKS Supported Amazon SageMaker Supported Amazon Web Services (AWS) Supported Anyscale Supported Apache Airflow Supported Azure Kubernetes Service (AKS) Supported Dask Supported Databricks Supported Docker Not Supported Feast Supported Google Kubernetes Engine (GKE) Supported Hugging Face Not Supported LanceDB Supported Python Supported Union Cloud Supported io.net Supported Show More Integrations View All 22 Integrations
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