GPU as a Service (GPUaaS) for AI

NovaGPU by IP ServerOne is a GPU as a Service (GPUaaS) platform that provides on-demand access to dedicated, non-shared NVIDIA GPUs hosted in Malaysia. Available GPU models include the NVIDIA RTX 3090, RTX 4090, RTX 5090, RTX 6000 Ada, RTX PRO 6000 Blackwell, and H200 NVL.

NovaGPU is designed for AI and machine learning workloads such as model development, fine-tuning, LLM inference, generative AI, RAG, computer vision, and high-performance computing (HPC). You can choose hourly or subscription plans based on your workload without purchasing physical GPU hardware upfront.

Your GPU infrastructure is managed by IP ServerOne and supported locally 24/7, with built-in backup capabilities and infrastructure hosted in Malaysia. This provides greater control over where your AI workloads and data are processed while supporting data sovereignty requirements.

GPU as a Service (GPUaaS) is a cloud-based platform that provides on-demand access to high-performance GPUs, eliminating the need for physical hardware. It enables businesses to run AI training, machine learning, and deep learning tasks without upfront costs or infrastructure management. NovaGPU offers flexible, cost-effective GPU instances that can be scaled to meet project demands. Simply sign up, select a plan, and start leveraging powerful GPUs instantly for your AI workloads.

GPU as a Service (GPUaaS) allows users to rent GPU instances on-demand through cloud providers like IP ServerOne. Once subscribed, users can easily spin up instances, scale resources, and pay only for what they use. This model eliminates the need for physical infrastructure, offering flexibility, performance, and accessibility for AI/ML workloads, data analytics, and simulations. With NovaGPU, you can select from various GPU models, the number of GPU cards, storage sizes, and more—all through a secure, managed platform, enabling you to focus on your AI projects.

Both Cloud GPUs and GPU as a Service (GPUaaS) provide access to GPU resources, but the key difference is how they are managed and accessed:

• Cloud GPU: Refers to a GPU hosted in the cloud, but it often requires manual management, configuration, and scaling, which can add complexity.
• GPUaaS: A fully managed service where the cloud provider handles infrastructure and maintenance, offering users a more flexible and streamlined experience. With NovaGPU, you get on-demand scaling, easy GPU instance management, and 24/7 support, specifically designed for AI and ML enthusiasts who prefer to focus on their projects without the hassle of managing infrastructure.

Both GPUaaS and dedicated bare metal GPUs offer powerful computing resources, but they differ in flexibility, cost, and management:

• GPUaaS: Provides on-demand, scalable GPU access with no long-term commitment, making it ideal for projects with fluctuating GPU needs. It offers lower costs and comes with managed services for hassle-free operation.
• Dedicated Bare Metal GPU: Offers exclusive access to a physical GPU on a dedicated server, delivering maximum performance for consistent workloads. However, it often comes with higher costs, limited scalability, and more management overhead.

With NovaGPU, you enjoy the flexibility of GPUaaS—high-performance GPUs on demand with no management burden.

GPU as a Service (GPUaaS) is the ideal solution for AI, large language models (LLMs), and deep learning due to the high computational power these tasks require. Unlike traditional CPUs, GPUs are built to handle complex algorithms and process large datasets in parallel, significantly speeding up tasks like model training, fine-tuning, and inference.

NovaGPU gives businesses access to dedicated NVIDIA GPU compute without the upfront investment of purchasing and maintaining physical GPU hardware. You can provision GPU resources based on your workload and choose between hourly or subscription plans.

Key benefits include:

• Dedicated GPU Resources: Every NovaGPU plan provides a dedicated, non-shared GPU card.
• Flexible GPU Pricing: Choose hourly or subscription plans based on your workload and usage requirements.
• Scalable AI Compute: Provision GPU resources for AI development, inference, fine-tuning, RAG, and other compute-intensive workloads.
• NVIDIA GPU Options: Choose from GPUs ranging from the RTX 3090, RTX 4090 and RTX 5090 to the RTX PRO 6000 Blackwell and H200 NVL.
• Malaysia-Hosted Infrastructure: Run your GPU workloads on infrastructure hosted in Malaysia, supporting data sovereignty requirements.
• Managed Infrastructure: IP ServerOne manages the underlying GPU infrastructure, so your team can focus on developing and running your applications.
• 24/7 Local Support: Get local technical support for your GPU infrastructure and workloads.

NovaGPU is suitable for developers, researchers, startups, and enterprises that need dedicated GPU compute for both short-term experiments and longer-running AI projects.

NovaGPU provides dedicated NVIDIA GPU compute for a wide range of AI, machine learning, and compute-intensive workloads. Common use cases include:

• AI Model Development & Fine-Tuning: Develop, experiment with, fine-tune, and benchmark machine learning and deep learning models.
• LLM Inference & Generative AI: Run open-source large language models (LLMs), text generation, AI agents, and other generative AI applications.
• RAG & Knowledge Assistants: Build retrieval-augmented generation (RAG) applications that connect LLMs with business documents and knowledge bases.
• AI Inference: Run trained AI models for applications such as classification, prediction, recommendation, and automation.
• Computer Vision & Video AI: Support image classification, object detection, visual inspection, video analytics, and other computer vision workloads.
• Data Processing & Analytics: Accelerate GPU-enabled data processing, analytics, and other compute-intensive workloads.
• Scientific Computing & HPC: Run simulations, research workloads, and other high-performance computing applications.
• 3D Rendering & Visualization: Support professional visualization, rendering, and other GPU-accelerated graphics workloads.

Yes. NovaGPU is designed to provide dedicated NVIDIA GPU compute for machine learning (ML), artificial intelligence (AI), deep learning, and generative AI workloads.

You can use NovaGPU for model training and fine-tuning, AI inference, LLM inference, RAG applications, computer vision, AI agents, and other GPU-accelerated workloads.

The range of available GPUs also lets you select GPU memory and compute resources based on your application’s requirements, from the RTX 3090, RTX 4090, and RTX 5090 through to higher-memory options such as the RTX PRO 6000 Blackwell and H200 NVL.

The right NovaGPU depends on your GPU memory requirements, model size, workload type, performance requirements, and budget. Different NVIDIA GPUs are suited to different AI, ML, visualization, and HPC workloads.

• NVIDIA RTX 3090: A practical option for AI development, experimentation, inference, RAG, and generative AI workloads.
• NVIDIA RTX 4090: Suitable for generative AI, RAG, model fine-tuning, inference, and AI development workloads.
• NVIDIA RTX 5090: Built on NVIDIA Blackwell architecture with 32GB GDDR7 memory, suitable for demanding generative AI, AI agents, model fine-tuning, and LLM inference workloads.
• NVIDIA RTX 6000 Ada: A professional GPU with 48GB GDDR6 memory, suitable for AI development and inference, computer vision, visualization, rendering, and engineering workloads.
• NVIDIA RTX PRO 6000 Blackwell: With 96GB GDDR7 memory, this GPU is suited to larger AI models, AI agents, LLM inference, RAG, professional visualization, and other memory-intensive AI workloads.
• NVIDIA H200 NVL: With 141GB HBM3e memory and high memory bandwidth, the H200 NVL is designed for large language models, generative AI, AI inference, RAG at scale, and high-performance computing.

If you’re unsure which GPU fits your workload, you can compare the GPU specifications, memory capacity, and intended use cases on the NovaGPU page or contact our team for assistance.

Security is a top priority for NovaGPU. We implement multiple layers of protection to ensure the safety and confidentiality of your data and workloads. Key security features include:

• End-to-End Encryption: All data is encrypted during transmission and storage to ensure secure handling.
• ISO & Compliance Standards: NovaGPU is hosted in an environment compliant with ISO 27001, ISO 27017, PCI-DSS, and SOC 2 Type II standards, ensuring adherence to industry security protocols.
• Data Redundancy: Your data is replicated across multiple data centers in Malaysia, enhancing reliability and minimizing the risk of data loss.
• Snapshot Backups: Automatic hourly, daily, and weekly snapshot backups safeguard your data from unexpected loss.
• DDoS Protection: Built-in DDoS protection protects your resources from external attacks, ensuring continuous operation.
• High Availability Architecture: NovaGPU is hosted on a high-availability, spine-leaf architecture, providing fault tolerance and near-zero downtime.
• User-Controlled Security: You can configure your own security rules to meet your specific requirements and safeguard your data.
• Data Sovereignty: Hosted locally in Malaysia, NovaGPU fully complies with data sovereignty regulations.

With NovaGPU, your sensitive AI projects are securely managed within a robust and reliable cloud environment.