Join WEKA At

ISC 2026

23 – 25 June, 2026
CCH – Congress Center Hamburg, Germany

Vendor Showdown

Modern HPC and AI workloads now run side by side under strict constraints on power, cost, footprint, and sovereignty.

In this fast-paced vendor showdown, join us for a provocative insight and open discussion on the future of data infrastructure. Discover how WEKA’s portfolio is purpose-built to eliminate data movement bottlenecks at global scale with a single high-performance platform for HPC, AI, and agentic workloads.

Delivering extreme throughput, high IOPS, and ultra-low latency, WEKA keeps CPUs and GPUs fully utilised in dense, efficient environments—without compromise on performance or scalability.

We’ll also share a sneak peek into what’s next, helping your organisation stay ahead of the curve in the era of sovereign, AI-driven infrastructure.

Shimon Ben David

Shimon Ben-David

CTO, WEKA

When: Tuesday, 23 June 2026
Time: 11:15 AM – 01:15 PM CET
Where: Hall Z – 3rd Floor
Type: Vendor Showdown

From Prototype to Production: WEKA for Scalable HPC & AI

Enterprise teams are moving beyond pilots to running HPC and AI at real scale—where inconsistent performance, runaway cloud costs, and underutilised GPUs quickly become business risks.

In this session, WEKA shows how Neuralmesh serves as the data foundation that enables production-scale HPC and AI, delivering the performance, consistency, and flexibility needed to keep accelerators fully utilised across on-prem and cloud environments.

Through real-world use cases—from AI workloads to genomics—we’ll demonstrate how Neuralmesh removes data bottlenecks, improves efficiency, and enables predictable cost and performance at scale.

The takeaway: at production scale, success in HPC and AI depends not just on compute—but on a data architecture built to keep it continuously fed.

Chris Ott

Chris Ott

Director of Sales Engineering – EMEA, WEKA

When: Wednesday 24 June 2026
Time: 3:00 PM – 3:20 PM CET
Where: Hall H, Booth L01 – Ground Floor
Type: HPC Solutions Forum

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