PowerGraph -Equitus KGNN improves speed, scale, and cost for on-premise AIX users: Webinar
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Financial, Healthcare and Gov/Def are areas where data sovereignty and on-premise security requirements prohibit the use of hyperscalers / cloud for mission-critical AI Deployment.
Regulated Industries on Power 10/11 require On-Premise Systems for Mission Critical AI Deployment. IBM AIX systems can connect to Ai without access to "cloud" in crucial problem in regulated areas, IBM Data Unification - Bridging Equitus.us PowerGraph (KGNN) connects IBM Power 11, and solutions like IBM Cloud Pak and Granite is specifically designed to address this by providing a highly efficient, secure, and integrated on-premise AI platform.
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Speed and Performance Improvements
KGNN's architecture is optimized to run natively on the IBM Power platform, eliminating bottlenecks common in other systems.
Power-Native Optimization: Equitus KGNN is a graph database built specifically to run natively on IBM Power10/11 and AIX, not as an emulated or containerized afterthought. This allows it to leverage the full compute power of the hardware.
On-Chip AI Acceleration: The IBM Power11 processor is designed with AI inferencing acceleration (Matrix Math Assist - MMA) baked directly into the CPU. KGNN uses this to run real-time AI workloads, like fraud detection and NLP, right next to the core transactional data, significantly reducing latency and increasing inferencing performance without requiring separate, complex GPU servers.
Automatic Data Unification: KGNN automatically connects, correlates, unifies, and contextualizes disparate data sets from fragmented data landscapes. This Auto ETL and semantic extraction eliminate the manual, time-consuming process of data preparation, allowing AI models to access high-quality, contextualized data faster.
Scale and Enterprise Capability
The joint solution is built for the high reliability and massive throughput required by regulated enterprises:
Scalable Knowledge Graph: KGNN builds a highly scalable, semantic knowledge graph data store that centralizes data from various sources (structured, unstructured, PDFs, etc.). This foundation provides the context, explainability, and traceability necessary for enterprise AI agents and models.
Built for Mission-Critical Uptime: IBM Power servers are known for their legendary Reliability, Availability, and Serviceability (RAS) features, often boasting 99.999% uptime. This stability is critical for regulated industries and allows for 24/7 operations, even when running intensive AI workloads.
AIX Security Integration: The combination of KGNN and the AIX operating system offers advanced virtualization, logical partitioning, and hardened security, which is essential for regulated environments to safeguard
critical enterprise workloads
Cost Efficiency
The design reduces both immediate hardware costs and long-term operational expenses:
Fewer GPUs Required: By leveraging the built-in AI acceleration (MMA) on the Power11 CPU, the solution often reduces or eliminates the need for expensive, dedicated GPU hardware for many AI inferencing tasks.
Performance Per Watt: Power11 is highly efficient, offering twice the performance per watt compared to comparable x86 servers, and includes an Energy Efficient Mode to reduce power usage during off-peak times. This translates to lower data center energy costs.
Consolidation and Licensing Economics: The powerful Power11 cores (with SMT8 and large cache) can run more workloads more efficiently. For licensed applications like Oracle DB, this high core efficiency can translate to better per-core licensing economics, lowering the Total Cost of Ownership (TCO).
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