GreenNode offers AI-ready infrastructure and applications using NVIDIA GPU technology. Features include pre-configured instances, full AI stacks, optimized storage, managed Kubernetes, high-performance networking, and API integration. The platform supports AI journey, expertise, and digital solutions across Southeast Asia, with deployment options like bare metal services and ML platforms.
Features
Pre-configured Instances
Offers ready-to-use computing instances optimized for AI tasks.
Full-stack AI Platform
Provides a comprehensive platform for building and deploying AI applications.
InfiniBand Network Service
Ensures high-performance connectivity with InfiniBand technology for data-intensive applications.
AI-centric Storage Service
Offers storage solutions optimized for AI workload demands.
Optimized Block Storage
Provides block storage solutions tailored for AI performance and efficiency.
Managed Kubernetes
Offers Kubernetes management for scalable and efficient AI deployments.
Top-notch API Experience
Delivers APIs optimized for seamless integration with AI applications.
Exceptional Backup Service
Provides robust backup solutions to secure AI data and models.
Customization
Tailor instances with GPUs, CPUs, RAM, and storage to fit your AI workloads.
High Performance
Infrastructure optimized for compute-intensive tasks with speeds up to 30X faster.
Digital Footprint across Southeast Asia
Provides data centers located in Vietnam, Thailand, and Malaysia to support local businesses with reliable and strong performance.
Top-Tier Security
Offers advanced security measures for data protection, ensuring businesses have a secure environment for operations.
Flexible Pricing
Adapts pricing models to fit various enterprise needs, allowing for efficient budget management.
All-Link Support
Provides support across all network links, ensuring seamless connectivity and minimum downtime.
High-Performance Storage
Delivers fast and reliable storage solutions to address enterprise performance demands.
Premium Networking
Ensures strong connectivity solutions that are optimized for high-speed, secure data transfers.
AI Computing Power
Offers powerful computing power for AI and Machine Learning, leveraging NVIDIA's HGX H100 in the Cloud.
Cost-Effective Hourly Rate
Provides access to NVIDIA HGX H100 starting at $2.34 per hour, making it scalable and affordable for various computational needs.
High Performance
Includes features like 7x efficiency improvements, 9x training AI models speed-up, and 30x AI recommendation throughput.
Flexibility and Scalability
Available at supercomputer scale, suitable for large-scale HPC and AI tasks, offering flexibility in deployment and usage.
High-end NVIDIA GPUs
Offers NVIDIA GH200, L40GS, and A40 GPUs for compute-intensive workloads. Provides tailored computing power with scalability.
Premium networking & Low latency
Ensures fast and reliable networking for compute tasks, reducing latency for better performance.
Multi-GPU Instances
Allows users to leverage multiple GPUs in a single instance for enhanced computing power and parallel processing.
Unlimited cloud storage
Provides limitless cloud storage options to store and manage large datasets required for AI and compute applications.
Absolute security
Offers robust security measures for data and workloads to ensure safety and integrity.
AI Notebook
Allows you to quickly build and train AI models using GPU acceleration. It includes features such as GPU notebook-based model training, integration of multiple NVIDIA products, and the ability to import/export datasets.
Model Training
Provides robust model training capabilities leveraging GPU acceleration for efficient and faster training of AI models.
Model Registry
Maintains a registry of all trained models for easy discovery, versioning, and deployment.
Online Prediction
Facilitates the deployment of AI models for live, online prediction tasks, enabling real-time data processing.
NVIDIA Preferred Partner
Recognized as NVIDIA partners in Southeast Asia with a specialization in GPU as a Service (GPUaaS) using optimized networking and storage.
Cost-Effective
Offers savings of up to 75% compared to other public cloud providers.
Enterprise Grade
Provides enterprise-grade solutions that handle the needs of both business and data operations.
LLM Training
Discusses the need for training large language models (LLMs) using distributed systems to handle the large datasets and complex calculations.
Single-Node Training
Explains how to set up and execute training jobs on a single node using the provided Orchestration framework.
Multi-Node Training
Covers setting up distributed training across multiple nodes, which can handle larger datasets and more complex models.
Docker and Singularity Containers
The article explains how to use containerization technologies like Docker and Singularity to manage environments and dependencies for training.
Python Script for Training
Provides a Python script for executing distributed training tasks, making it easier for developers to implement the training workflow.
RAG System Overview
The blog explains Retrieval-Augmented Generation (RAG), a system combining retrieval and generation tasks for improved AI responses to queries.
Embedding Models in RAG Systems
Highlights the importance of embedding models in RAG systems, which help in mapping queries and documents into vectors for efficient retrieval.
Dense vs Sparse Representation
The article describes the difference between dense and sparse representations used in embedding models for processing and retrieving information.
Advantages of Using Embedding Models
Discusses the benefits of embedding models, such as improved accuracy in information retrieval and better handling of complex queries.
Challenges and Considerations
Outlines challenges faced in implementing embedding models, including computational costs and the need for large datasets.
Future Trends
Explores future trends in embedding models and RAG systems, emphasizing advancements in model architectures and training techniques.
CPU Instances
Offers on-demand virtual machines optimized for LLM training tasks like data preprocessing and inference. These instances are cost-effective alternatives to GPU instances for certain workloads. Two configurations are offered: cpu-small-24-4v (24 vCPUs, 48 GB memory) and cpu-general-48-8 (48 vCPUs, 96 GB memory).
Network Volumes
Provides high-performance, scalable storage solutions for tasks like gaming, spyware, malware detection, and video streaming. Designed to be accessed easily and mounted to virtual machines.
SSH Access
Allows secure and direct access to CPU instances for better control and troubleshooting. Enables users to run commands on their virtual machines securely through SSH.
Auto-scaling Infrastructure
Automatically scales the computational resources based on the workload requirements to optimize performance and cost.
Integrated Development Environment (IDE) Support
Supports popular IDEs like Jupyter and PyCharm, allowing developers to work in familiar environments.
Model Monitoring and Management
Provides tools to monitor models in production and manage their deployments effectively.
Seamless Data Integration
Enables easy integration with various data sources, facilitating streamlined data processing and management.
Optimized GPU Usage
Utilizes GPUs efficiently to accelerate model training and inference, thereby reducing computation time.
AI GPU Cluster
Thailand's first hyper-scale AI GPU cluster, launched by GreenNode in partnership with NVIDIA, located at STT Data Center. The cluster aims to enhance AI computational capabilities in the region.
NVIDIA Partnership
Collaboration with NVIDIA to integrate their A100 Tensor Core GPUs, which are designed for AI and machine learning tasks.
Environmentally Friendly
The AI cluster is designed with energy efficiency in mind, aiming to reduce carbon footprints and encourage greater sustainability in AI operations.
Scalability
The cluster offers scalability options for businesses looking to expand their AI infrastructure securely and efficiently.