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:
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Growing Demand for AI, Machine Learning and LLM
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Rising popularity of cloud gaming
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Growth in Data Analytics and Real-Time Processing Workloads
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Infrastructure and Operational Cost Savings
Benefits of GPUaaS
The key benefits of GPU-as-a-service for businesses include:
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Scalability: Organisations can easily adjust their GPU resources to align with project demands for seamless scaling to meet data-driven and compute-intensive workloads.
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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.
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Data Security: GPUaaS providers typically implement robust security measures to protect sensitive data so businesses can use cloud resources without compromising security.
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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:
- Latency: GPUaaS depends on internet connectivity, which may introduce latency, especially for applications requiring real-time processing.
- Compatibility: Some legacy systems or custom configurations may require additional effort to migrate to GPUaaS.
- 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
Some of the popular GPU as a Service providers could be Hyperstack, NexGen Cloud’s GPUaaS platform, lets you deploy workloads on NVIDIA GPU infrastructure, paying only for usage. Here's why it's ideal:
- Access to Cutting-Edge GPUs: As an NVIDIA Preferred NCP Partner, we provide advanced GPUs for various workloads, from AI to big data.
- Flexible Pricing: With minute-by-minute billing, pay only for what you use. No hidden fees, and options for reservations and hibernation reduce costs.
- Easy Deployment: Our platform offers 1-click deployment, simplifying setup so you can focus on projects.
- Advanced Storage and Networking: We provide high-performance storage and Ethernet with up to 16 Gbps inter-VM bandwidth, reducing latency and boosting throughput.
- Seamless Scaling with NVLink: NVLink supports 600 GB/s bandwidth for high-end NVIDIA GPUs, crucial for large ML and AI projects.
- Support for Open-Source Models: Hyperstack supports open-source AI models, allowing integration of various tools and frameworks. Deploy models like Meta's Llama 3 easily.
- Security and Control: We prioritise security with role-based access control and advanced firewall rules for a secure 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.
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21 Feb 2025