Top 5 reasons to run AI workloads on IBM Power

Foundation models are bringing an inflection point in AI... ...but how enterprises adopt and execute will define whether they unlock value at scale. And, as AI becomes a regular operational necessity, IT platforms must be built for AI.

Here’s just 5 reasons why your clients should consider running AI workloads on IBM Power to transform their organisation…

1.????? Accelerate efficiently: Leverage IBM Power servers—with their AI-optimized hardware, large memory, high parallelism, on-chip acceleration and AI-optimized software—to provide superior performance for your AI workloads. Data scientists can fully use IBM Power platform capabilities without requiring any change to their code. For large language AI models, process up to 42% more batch queries per second on IBM Power S1022 servers than compared x86 servers during peak load of 40 concurrent users and enjoy inferencing latency below one second.

2.????? Converge AI with data: Deploy AI with enterprise mission-critical processes, data and transactions that resides on IBM Power servers. This convergence allows you to:

– Streamline IT operations with simplified architectures

– Minimize exposure and risks by keeping the data within regulatory compliant boundaries

– Reduce latency by bringing AI to data.

3.????? Safeguard insights: With IBM Power servers, safeguard AI insights without impacting performance using transparent memory encryption and protect AI workloads with security at every layer of the stack. Scale AI inferencing for complex tasks such as generative AI with reliable performance. IBM Power10 has 4 times cryptography engines in every core, and IBM Power is 60 times more secure than unbranded commodity servers and provides 99.999999% uptime for best-in-class reliability.

4.????? Hybrid flexibility: Hybrid flexibility is critical when it comes to deploying AI workloads. IBM Power provides that flexibility, enabling enterprises to harness the power of AI both on-premises and in the cloud with IBM Power Virtual Server. In addition to environment flexibility, choice matters for higher levels of the AI solution stack. IBM Power supports multiple AI-optimized software options including:

– Enterprise

– Open-source, community supported

– Open-source, enterprise supported

5.????? Sustainable and on-demand infrastructure: Meeting sustainability requirements combined with cost-optimized infrastructure to deploy evolutionary AI workloads is a challenge. IBM Power E1050 provides comparable performance and uses 50% less energy at maximum input power than the compared x86-based server5, allowing clients to run the same work with lower energy usage. At the same time dynamic capacity on IBM Power servers helps clients reduce capital expenditures and procurement costs that can help contribute to lower TCO. Dynamic consumption provides many of the attributes that clients like about public cloud in an on-premises, private cloud with better control and security.

Message me to find out more about how you can support your clients to accelerate AI efficiently with IBM Power.