Amazon SageMaker HyperPod: Reduce costs with new governance capability-AIM388-NEW
Summarize of the Video Transcription
Introduction
Kareim, a product manager at Amazon Web Services, discusses the recent launch of Amazon SageMaker HyperPod Task Governance.
The session aims to address the challenges faced by companies with the advent of generative AI and the growing demand for accelerated computing resources.
Challenges Faced by Customers
Data collection and preparation for training large-scale generative AI models.
Provisioning and managing the availability of clusters for data scientists to run their training models.
Ensuring the stability of the infrastructure and enabling distributed training strategies to accelerate the training process.
Amazon SageMaker HyperPod
Amazon SageMaker HyperPod was launched last year to address these challenges.
HyperPod provides a resilient environment with self-healing capabilities, enabling easier distributed training and better control over resource utilization.
This resulted in a reduction of training time by up to 40% for customers.
Introducing HyperPod Task Governance
Despite the success of HyperPod, customers faced new challenges:
Static allocation of compute resources to teams, leading to under- and over-utilization.
Lack of visibility into real-time utilization and the inability to prioritize tasks.
Reduced data scientist productivity and increased costs due to the need for more compute resources.
Amazon's internal teams, including the Amazon Retail and Amazon AI teams, faced similar issues.
Amazon's Internal Innovation
Joy, from Amazon's central efficiency team, discussed the internal solution they developed to address these challenges.
They built an internal service to pool all the accelerated compute resources and use a dynamic scheduling algorithm to maximize utilization across all projects and teams.
The solution provided features for resiliency, such as regular health checks, automatic resubmission of failed jobs, and real-time utilization metrics.
This enabled Amazon to achieve over 90% utilization across their teams, addressing the challenges of high demand, low supply, and low utilization.
Amazon SageMaker HyperPod Task Governance
Inspired by the internal innovation, Amazon launched SageMaker HyperPod Task Governance to bring these capabilities to customers.
Key features:
Dynamic allocation of compute resources across teams, while maintaining budgets.
Prioritization of high-priority tasks during resource contention.
Real-time monitoring and governance of compute resource utilization.
Common use cases:
Resource management and dynamic allocation.
Task orchestration and prioritization.
Real-time monitoring and cost optimization.
Live Demo
Kareim walked through a live demo of the SageMaker HyperPod Task Governance feature, showcasing its capabilities:
Defining team allocations and policies for task prioritization and idle compute allocation.
Observing real-time task execution and resource utilization.
Handling scenarios where teams exceed their allocated compute and borrow from idle resources.
Preempting lower-priority tasks to accommodate higher-priority tasks.
Customer Testimonial
Sham Kumar from Articulate AI shared their experience using SageMaker HyperPod Task Governance to accelerate their AI platform development.
Articulate AI faced challenges in managing compute resources and fine-tuning models at scale, which were addressed by the features of SageMaker HyperPod Task Governance.
The solution enabled Articulate AI to launch a new SaaS product, Articulate Essential, in a compressed timeline of 2-3 months, which would not have been possible without the capabilities of SageMaker HyperPod Task Governance.
Conclusion
Amazon SageMaker HyperPod Task Governance aims to help customers maximize the utilization of their accelerated computing resources while reducing costs.
Key capabilities include dynamic resource allocation, task prioritization, real-time monitoring, and governance, leading to improved data scientist productivity and cost optimization.
These cookies are used to collect information about how you interact with this website and allow us to remember you. We use this information to improve and customize your browsing experience, as well as for analytics.
If you decline, your information won’t be tracked when you visit this website. A single cookie will be used in your browser to remember your preference.