Optimizing AI Inference and Governance with Wallaroo on IBM® Power®
5 min read
By Younes Amar
Intro
The surge in AI adoption across all industries, such as retail, manufacturing, and financial services, is astounding. Businesses are looking to capitalize on the power of AI to drive improvements in operational efficiency, market differentiation, and data-driven decision-making in pursuit of increased revenues and market share. However, adopting AI does not come without its challenges. To combat these challenges, Wallaroo.AI built an inference platform for turnkey optimized AI inference, agnostic to model types and hardware, that can quickly support newer models (e.g., the next DeepSeek) efficiency. Recently, Wallaroo.AI partnered with IBM® to further help enterprises reduce the time and cost it takes to get their AI applications working. IBM® Power® is known for high-performance computing, scalability, and enterprise-grade features, ideal for various AI workloads. Optimized for IBM Power, Wallaroo.AI provides prospective clients with a clear path to rapidly achieve their strategic AI business goals. Enterprises that have invested in Power can leverage their existing infrastructure to enable AI initiatives, maximizing performance and efficiency with Wallaroo’s inference platform.
AI Production Challenges
The challenges enterprises face in delivering ROI from AI projects are multifold. Investing in new GPU infrastructure, specifically for AI inference workloads, significantly strains a lean CapEx budget. Efficiently deploying AI models is crucial for achieving quick value realization and managing costs effectively, but it is not easy to accomplish without the right resources. Another challenge enterprises face is leveraging distributed AI workloads to accelerate AI adoption while maintaining data and AI governance in decentralized environments. Data can be, and often is, distributed across an enterprise ecosystem, making it challenging to get the most value out of these resources while staying on top of the fundamentals of security, privacy, and model performance. The complex multi-modality of enterprise data in everyday use cases such as Computer Vision and GenAI poses significant difficulties.
Solution
Enterprises that have invested in IBM Power infrastructure are well-positioned to overcome these challenges with an extensive ecosystem of tools and libraries available to confidently ship AI to production. Deeply integrated into the IBM Power ecosystem, Wallaroo enables enterprises to leverage AI inference capabilities on IBM Power. IBM Power clients can quickly modernize with Wallaroo to run high-performance Computer Vision and GenAI workloads in the cloud, on-prem, and at the edge without compromising on AI governance, operational efficiency, and costs. How does the combination of IBM’s Power10 infrastructure and Wallaroo work for enterprise AI teams?
Turnkey AI Inference
Wallaroo has an Intuitive UI and SDK that empowers AI teams to autopackage and deploy standard and custom AI inference microservices effortlessly to run on IBM Power within the cloud, on-prem, or at the edge. AI teams can take the crucial first step from prototype into production without any heavy low-level infrastructure manipulation required for model packaging or optimization on IBM Power. Autopackaging ensures that the model is consistent, portable, scalable, and reproducible across different platforms and environments. With Wallaroo, this capability supports the flexibility of any model deployed across any hardware architecture (e.g., Power) and associated acceleration libraries (e.g., MMA) for AI inference. Learn more about Wallaroo’s Autopackaging capability.
AI Inference Optimization
Once models are deployed, AI teams still need to optimize AI inference microservices to help control the potentially high AI operational costs that can derail a project. Wallaroo’s high-performance inference engine is designed to help AI teams easily achieve optimized performance through built-in data and memory management efficiencies, autoscaling, and concurrent batching capabilities to maximize hardware utilization and performance in large-scale scenarios while minimizing latency. Learn more about Wallaroo’s Inference Optimization Performance capabilities.
Performance
Several performance tests were conducted to quantify the capabilities of Wallaroo running on IBM Power. Results revealed that inference latency and throughput were 2x as effective when combining IBM Power and the Wallaroo Inference Engine for Computer Vision models and LLMs.
Inference Latency
Inference Latency tests with Computer Vision Applications revealed that Wallaroo on Power10 introduces an additional 2x performance boost on AI inference latency and throughput. Throughput test run results in the chart below show 2x more throughput scaling for CV Models on IBM Power10 with Wallaroo. Throughput test results in the chart below show up to 2x more throughput for Llama.cpp on IBM Power10 with Wallaroo.
Lifecycle Management and Governance
Once AI teams deploy and optimize their models, keeping them accurate and reliable is ongoing. Regardless of where AI inference is happening, in the cloud, on-prem, or at the edge, the distributed nature of production AI should not limit the best practice of model observability for proactive management and governance. Wallaroo’s built-in centralized management and monitoring capabilities equip AI teams with built-in alerts and advanced model observability metrics, providing real-time insights into model performance. If a model, whether Computer Vision or LLM, starts to drift, data scientists and AI engineers can immediately be alerted and take proactive measures to validate and update models in Wallaroo without causing any interruptions to the existing deployment in place.
In the race to adopt AI, enterprises across many verticals with existing investments in IBM Power can stride confidently from prototype to AI production workloads with Wallaroo’s turnkey AI inference optimized on Power10. With IBM and Wallaroo, Enterprise AI teams can deploy a variety of open source Computer Vision and LLM models with maximized performance, efficiency, and versatility on IBM Power, overcoming the common challenges faced in leveraging distributed AI workloads for accelerating AI adoption while maintaining data and AI governance for faster ROI. Wallaroo.AI partners with customer teams to efficiently validate, deploy, and scale AI initiatives. Offering repeatable, industrial-grade operationalization capabilities to realize:
