What is GPUaaS (GPU-as-a-Service): Here’s What You Need to Know

Traditional GPU infrastructure requires significant investment in physical hardware leading to high upfront costs due to ongoing maintenance, upgrades and electricity. With GPUaaS, companies can eliminate the need for upfront hardware investments and convert GPU usage into an operational expense, paying only for what they use. Continue reading as we explore what GPU-as-a-Service means, its key benefits and why Hyperstack can be your preferred GPUaaS provider.  

What is GPUaaS? 

GPU-as-a-Service (GPUaaS) allows users to access and deploy GPUs in the cloud rather than purchasing and maintaining them on-site. With GPUaaS, companies can run large-scale AI training, ML models, deep learning, data analytics and HPC applications by leveraging cloud GPUs on demand. This eliminates the need for substantial upfront investments in GPU hardware and offers flexible billing models that make it affordable for companies of all sizes. 

On-Premises GPUs vs. GPUaaS 

On-premises GPUs offer full control over hardware, reduced latency and predictable performance, making them suitable for organisations with long-term GPU needs. However, they require significant upfront investment, ongoing maintenance and upgrades with high energy consumption. While GPU-as-a-Service (GPUaaS) eliminates upfront costs by offering on-demand access to powerful GPUs with flexible pricing models to ensure scalability for fluctuating workloads. 

Growth Drivers Behind GPUaaS 

In 2023, the global GPU-as-a-service market was valued at $3.23 billion and is expected to increase from $4.31 billion in 2024 to $49.84 billion by 2032 [source]. This massive growth is driven by the following factors: 

• Growing Demand for AI, Machine Learning and LLM 

• Rising popularity of cloud gaming 

• Growth in Data Analytics and Real-Time Processing Workloads 

• Infrastructure and Operational Cost Savings  

Benefits of GPUaaS 

The key benefits of GPU-as-a-service for businesses include: 

1. Scalability: Organisations can easily adjust their GPU resources to align with project demands for seamless scaling to meet data-driven and compute-intensive workloads. 

2. Flexible Payment: GPUaaS offers a pay-as-you-go pricing model so businesses pay only for the GPU resources they consume, which helps manage budgets more effectively. 

3. Data Security: GPUaaS providers typically implement robust security measures to protect sensitive data so businesses can use cloud resources without compromising security. 

4. Faster Time-to-Market: With on-demand access to powerful GPU resources, companies can accelerate their development cycles and bring products to market more quickly, gaining a competitive edge.

Challenges of GPUaas

Despite its advantages, GPUaaS also presents certain challenges that you should be aware of:

1. Latency: GPUaaS depends on internet connectivity, which may introduce latency, especially for applications requiring real-time processing.
2. Compatibility: Some legacy systems or custom configurations may require additional effort to migrate to GPUaaS.
3. Data Transfer Costs: While Hyperstack avoids ingress/egress fees, data-heavy workloads on other platforms might incur significant transfer costs.

Why Choose Hyperstack as Your GPUaaS Provider 

Hyperstack is NexGen Cloud’s GPU-as-a-service platform where you can easily deploy any workload in the cloud on the latest NVIDIA enterprise-grade infrastructure and only pay for what you consume. Here’s how Hyperstack could be the ideal GPUaaS provider for you: 

Access to Cutting-Edge GPUs for Any Workload 

As an NVIDIA Preferred NCP Partner, we offer access to advanced NVIDIA GPUs designed to handle demanding workloads. You have the flexibility to choose the best GPU for your specific workload needs, from AI model training and AI Inference to big data processing and rendering. Our VMs are all optimised for AI workloads, with advanced storage options and high speed networking available up to 350 Gbps for 

NVIDIA H100 SXM

NVIDIA H100 PCIe

NVIDIA RTX A6000

NVIDIA A100

Below are the NVIDIA A100 VM configurations offered in the Canada region (latest generation):

Below are the NVIDIA A100 VM configurations offered in the Norway region (older generation):

NVIDIA L40

Flexible Pricing Model 

With Hyperstack’s minute-by-minute billing, you only pay for the exact time you use the resources. Our GPU Pricing model is free of hidden charges and there are no ingress or egress fees. We offer reservation options for businesses that need consistent access to GPU resources to scale. We also offer hibernation options so you can pause your workloads when they are not in use. This can reduce your operational costs.  

Flexible Deployment 

Our cloud platform is designed for ease of use, featuring 1-click deployment options that allow users to get their workloads up and running instantly. This feature removes complexities and lets you focus on your projects rather than worrying about the setup process. 

Advanced Storage and High-Speed Networking 

We offer high-performance storage options, including NVMe block storage which significantly improves workload performance. To enhance speed, all our GPUs are equipped with Ethernet supporting up to 16 Gbps inter-VM bandwidth. Our latest high-speed networking with up to 350 Gbps which is optional for users, reduces latency and boosts data throughput, making it ideal for AI inference, HPC and data analytics. 

Seamless Scaling with NVLink 

Hyperstack supports NVLink for GPU-to-GPU communication of 600 GB/s bidirectional bandwidth on high-end NVIDIA GPUs like the NVIDIA H100 PCIe and NVIDIA A100, which allows for higher data throughput. This is essential for large-scale ML and AI projects as NVLink ensures that projects with heavy data-transfer requirements can operate seamlessly without bandwidth limitations. 

Support for Open-Source Models 

Hyperstack is committed to supporting open-source AI models. Our platform ensures that users are not restricted by vendor lock-ins. You can integrate various open-source tools, libraries and frameworks, any solution that best meets your project needs. You can also deploy and run the latest open-source models, including Meta's Llama 3 on Hyperstack. Interested in getting started? Explore our tutorials below: 

• Deploying and Using Granite 3.0 8B on Hyperstack
• Deploying and Using Llama-3.1 Nemotron 70B on Hyperstack
• Deploying and Using Llama 3.2 11B on Hyperstack
• Deploying and Using Notebook Llama on Hyperstack
• Deploying and Using Stable Diffusion 3.5 on Hyperstack
• Deploying and Using Flux.1 on Hyperstack

Security and Control 

Security and control are paramount when using cloud solutions. Hyperstack prioritises these aspects by incorporating strong measures to protect your data and maintain compliance. 

• Role-Based Access Control: We have built-in access control features that ensure only authorised users have the appropriate permissions to access GPU resources.  
• Advanced Firewall Rules: With Hyperstack, advanced firewall rules are in place to create a secure and compliant infrastructure.
  

Explore the Hyperstack GPU Cloud Platform 

Ready to experience the future of GPU-as-a-Service? Take a quick tour of the Hyperstack below and discover how to get started on our cloud platform. 

Conclusion 

The need for scalable and efficient AI solutions has never been higher. GPU-as-a-Service provides a powerful solution for organisations seeking to adopt AI at scale. By choosing Hyperstack’s GPUaaS platform, you not only benefit from an efficient and secure platform but also support a commitment to sustainability. Our Green Cloud operations in Europe and North America ensure that high-performance workloads are executed with minimal environmental impact. Together, we can accelerate the adoption of AI technologies efficiently and sustainably.  

Sign Up Now to Get started with Hyperstack.  

FAQs 

What is GPU-as-a-Service? 

GPUaaS allows users to access and deploy GPU resources in the cloud, eliminating the need for on-premises hardware and providing flexible billing options. 

What are the main benefits of using GPUaaS? 

The key benefits of using GPUaas include scalability, flexible payment models, enhanced data security, and faster time-to-market for AI and ML applications. 

Can I scale my GPU resources with Hyperstack? 

Yes, Hyperstack allows seamless scaling of GPU resources to meet changing workload demands, ensuring optimal performance. 

How do I get started with Hyperstack? 

Sign up for a Hyperstack account by visiting https://console.hyperstack.cloud/. After registration, sign in, activate your account and add credit to deploy your virtual machine on Hyperstack. Learn more about getting started in our documentation here.