About this event
As AI models continue to grow in size and context windows expand, GPU memory has become a critical limitation for achieving fast, efficient inference. When context memory capacity is exceeded, organizations experience increased latency, context recomputation, reduced throughput, and lower GPU utilization.
Join MinIO and NVIDIA for a technical discussion on how MinIO MemKV addresses the growing challenge of inference context memory, including the underlying infrastructure demands of AI inference.
Learn how MemKV provides a distributed, high-performance context memory layer that extends GPU memory capacity using RDMA-connected, memory-mapped NVMe storage.
Attendees will learn how MinIO MemKV:
Date/Time:
September 17, 2026
Time: 1:00 pm (EDT), 10:00 am (PT)
Hosted by
Patrick Riel is a Storage DevTech with more than a decade of experience across cloud, data center, and Kubernetes environments. His work spans networking, storage, AI, and infrastructure, with a focus on agentic AI, open-source contributions, and inference acceleration using technologies such as NVIDIA Dynamo, NIXL, and KV cache offloading. Outside of work, Patrick is an avid golfer and skier.
Expertise level technical instruction and curriculum design for object storage, enterprise Linux, and related technologies, including security, distributed computing, AI/ML, clustering, and performance. Previously an engineer at Sun Microsystems and Red Hat.
MinIO is the data and memory foundation for enterprise AI. AIStor and MemKV unify the data stack, from agentic memory to tables and objects across core, edge, and cloud, built for AI-scale speed and economics. Trusted by 77% of Fortune 500, MinIO helps AI agents unlock the value of enterprise data.
