In today's rapidly evolving digital landscape, businesses are increasingly relying on AI and high-performance computing (HPC) to drive innovation and growth. However, meeting the compute requirements and demands of AI lifecycle can be challenging, especially when it comes to procurement and deployment of hardware. This is where IBM Cloud comes into play, offering a comprehensive solution that caters to the diverse needs of AI lifecycle.

The AI lifecycle comprises three main stages: Prepare, Build, and Deployment. Each stage requires different compute capabilities. For instance, data filtering and curation, which fall under the Prepare stage, can be handled by low to mid-end CPUs. On the other hand, training and model validation, part of the Build stage, necessitate high-end  NVIDIA H100 Tensor Core GPUs due to their long-running and compute-intensive nature. During Deployment, while performance depends on a number of factors including model size and performance constraints, the NVIDIA H100 or NVIDIA L40S offer good performance for model adaptation/fine-tuning and inferencing, and L40S and NVIDIA L4 Tensor Core GPUs are great for small model inferencing.

Given these varying requirements, cloud computing emerges as the ideal solution. As the old adage goes, “why buy a car to drive it one month a year when you can rent it?” Similarly, purchasing GPUs for occasional use may not be the most cost-effective approach. Moreover, the current global shortage of GPUs further underscores the benefits of cloud computing. With high lead times to purchase GPUs, businesses can ill afford to wait.

IBM Cloud, in collaboration with AI platform providers like NVIDIA and Intel, offers a robust GPU as a Service offering providing a complete and flexible lineup of accelerated computing offerings to leverage during every stage of an enterprise’s AI implementation. Offering access to a wide range of GPUs, including NVIDIA H100 Tensor Core GPU, which are already available in IBM Cloud's Canadian Data Centres. Furthermore, Intel Gaudi 3 AI Accelerators will soon be available across IBM Cloud's Multi Zone Regions. This aims to help customers more cost-effectively scale enterprise AI workloads, while prioritizing performance, security and resiliency.

IBM Cloud's commitment to security is another significant advantage. The platform applies multi-level security protocols designed to protect AI and HPC processes and guard against data leakage and privacy concerns. It also includes built-in controls to establish infrastructure and data guardrails for AI workloads.

For Canadian businesses, the benefits extend beyond computational power and security. Here are five key advantages:

1. Data Residency: By keeping AI data within Canada, businesses can meet their data residency requirements, ensuring compliance with local regulations.

2. Data Control and Ownership: Businesses can maintain control over their data and keep it secure using IBM Cloud’s enterprise security features such as Keep their Own Key, FIPS 140-Level 4, amongst others.

3. Speed of AI with On-Premise Data: Local data processing enables faster AI computations, enhancing the speed of AI operations while augmenting with cloud services closely located to where you are.

4. Open Source and Open Model AI: IBM Cloud supports the deployment of open source and open model AI, fostering innovation and flexibility.

5. Investment in Canada: By leveraging IBM Cloud, businesses can contribute to Canada's growing tech ecosystem.

IBM Cloud's infrastructure for AI offers a powerful and versatile solution for Canadian businesses navigating the AI landscape. With its comprehensive GPU offerings, robust security measures, and commitment to data sovereignty, IBM Cloud stands out as a preferred choice for businesses seeking to harness the power of AI and HPC.

Learn More

As part of IBM’s mission to make AI for business more accessible, IBM watsonX leverages IBM's GPU capabilities on IBM Cloud. For more information on IBM’s GPU capabilities, please visit HERE.