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Description

Accelerate computational tasks such as those found in machine learning and high-performance computing (HPC) with a diverse array of GPUs suited for various performance levels and budget constraints. With adaptable pricing and customizable machines, you can fine-tune your setup to enhance your workload efficiency. Google Cloud offers high-performance GPUs ideal for machine learning, scientific analyses, and 3D rendering. The selection includes NVIDIA K80, P100, P4, T4, V100, and A100 GPUs, providing a spectrum of computing options tailored to meet different cost and performance requirements. You can effectively balance processor power, memory capacity, high-speed storage, and up to eight GPUs per instance to suit your specific workload needs. Enjoy the advantage of per-second billing, ensuring you only pay for the resources consumed during usage. Leverage GPU capabilities on Google Cloud Platform, where you benefit from cutting-edge storage, networking, and data analytics solutions. Compute Engine allows you to easily integrate GPUs into your virtual machine instances, offering an efficient way to enhance processing power. Explore the potential uses of GPUs and discover the various types of GPU hardware available to elevate your computational projects.

Description

HPC-AI is a cutting-edge enterprise AI infrastructure and GPU cloud service crafted to enhance the training of deep learning models, facilitate inference, and manage extensive compute tasks with impressive performance and cost-effectiveness. The platform offers an AI-optimized stack that is pre-configured for swift deployment and real-time inference, adeptly handling demanding tasks that necessitate high IOPS, ultra-low latency, and significant throughput. It establishes a strong GPU cloud environment tailored for artificial intelligence, high-performance computing, and various compute-heavy applications, equipping teams with essential tools to execute complex workflows effectively. Central to the platform's offerings is its software, which prioritizes parallel and distributed training, inference, and the fine-tuning of expansive neural networks, aiding organizations in lowering infrastructure expenses while preserving high performance. Additionally, technologies like Colossal-AI contribute to its capabilities, drastically speeding up model training and enhancing overall productivity. This combination of features helps organizations remain competitive in the rapidly evolving landscape of artificial intelligence.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Docker No 
Google Cloud Managed Service for Apache Spark Yes 
Google Cloud Platform Yes 
Google Compute Engine Yes 
Google Kubernetes Engine (GKE) Yes 
Hugging Face No 
Kubernetes No 
NVIDIA DRIVE Yes 
PyTorch No 
TensorFlow No 

Integrations

Docker Yes 
Google Cloud Managed Service for Apache Spark No 
Google Cloud Platform No 
Google Compute Engine No 
Google Kubernetes Engine (GKE) No 
Hugging Face Yes 
Kubernetes Yes 
NVIDIA DRIVE No 
PyTorch Yes 
TensorFlow Yes 

Pricing Details

$0.160 per GPU
Free Trial Yes 
Free Version No 

Pricing Details

$3.05 per hour
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/gpu

Vendor Details

Company Name

HPC-AI

Country

Singapore

Website

www.hpc-ai.com

Product Features

HPC

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives