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 provides on-demand, high-performance GPUs, ranging from mid-tier options like the RTX 3090 and RTX 4090 to top-tier models like the RTX 6000 Ada and NVIDIA H200 NVL. Key benefits include:

• Scalable GPU Resources: Easily spin up and scale your GPU instances as needed, supporting both short-term and long-term AI workloads.
  
• Flexible Pricing: Choose between pay-per-hour or subscription-based models, allowing you to pay only for what you use or secure long-term cost savings with a subscription—ideal for sustaining prolonged AI projects without breaking the bank.
  
• Optimized for AI: Perfect for training, fine-tuning, and running small-to-mid-sized AI models, including inference, helping you get the most from your AI initiatives.
  
• Fully Managed: No need to manage infrastructure—IP ServerOne handles everything, freeing up your resources to focus on innovation.
  
• Local Cloud Hosting: Hosted in a secure local cloud environment, ensuring data sovereignty compliance, which is crucial for businesses with strict data privacy requirements.
• Maximized ROI: With flexible pricing, scalability, and high-performance GPUs, NovaGPU ensures that your investment in AI technologies remains cost-effective, delivering strong ROI even for long-term projects.

NovaGPU is ideal for tasks requiring moderate computational power, particularly for AI, machine learning (ML), and deep learning applications. Key use cases include:

• AI Model Training & Fine-Tuning: Ideal for training and fine-tuning small-to-mid-sized AI models, NovaGPU helps accelerate processing without the need for expensive hardware.
• AI Inference: Run inference tasks on trained models efficiently, making real-time predictions or classifications for a wide range of applications.
• Data Processing & Analytics: Handle medium-scale data processing tasks and analytics with NovaGPU, providing faster results for your AI-driven projects.
• Small to Mid-Sized Simulations: Run computationally intensive simulations, such as those used in research or product development, at a fraction of the cost of more powerful alternatives.

With NovaGPU, you get an on-demand, cost-effective, and secure GPU solution tailored to support your small-to-mid-sized AI and ML projects, maximizing performance without overcommitting resources.

Yes, NovaGPU is specifically designed to support machine learning (ML) and AI projects. With its on-demand, scalable GPU instances, NovaGPU provides the computational power needed for tasks like training, fine-tuning, and inference of AI models. Whether you are working on small-to-mid-sized AI models or data processing, NovaGPU delivers high performance at an affordable cost. It’s a perfect fit for developers, researchers, and businesses looking to accelerate their AI and ML workflows without investing in expensive infrastructure.

Choosing the right GPU instance for your workload on NovaGPU depends on your project’s size, complexity, and budget. At IP ServerOne, we offer both bare metal GPUs and GPU as a Service through NovaGPU, tailored for different AI/ML applications. Here’s a guide to help you select the ideal GPU:

• RTX 3090: A budget-friendly option for smaller AI projects like image recognition and basic models. Ideal for beginners or small teams starting out in AI.
• RTX 4090: A powerful and efficient choice for handling larger models and datasets. Great for solo developers or growing projects needing strong computing power.
• RTX 6000 Ada: A professional-grade GPU with extra memory and stability, perfect for businesses and professionals running advanced AI applications.
• H200 NVL: The top-tier GPU for large-scale AI research, enterprise-level projects, and demanding workloads, providing unmatched processing power for high-end AI development.

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.