# VAST Data Expands Collaboration with AMD to Advance AI Infrastructure for the Inference Era — retained record

> Retained news record from news:hpcwire.

Canonical: https://highsignal.app/data/records/11c6c3f4a3e2d051

[← sources](https://highsignal.app/data)


source: [news](https://highsignal.app/data/news) (news:hpcwire)  published 2026-07-24 18:25 ingested 2026-07-25 07:57

[original source ↗](https://www.hpcwire.com/off-the-wire/vast-data-expands-collaboration-with-amd-to-advance-ai-infrastructure-for-the-inference-era/)

## retained text



```
Off the Wire Press Releases
July 24, 2026 – VAST Data has announced an expanded collaboration with AMD to help AI cloud providers and enterprises build and operate high-performance AI factories at scale. The collaboration brings together the VAST AI Operating System with 6th Gen AMD EPYC CPUs and AMD Instinct GPUs to support scalable training, inference and agentic AI workloads with improved efficiency, flexibility and performance.
As organizations move beyond model training and begin operationalizing AI agents, reasoning systems and large-scale inference services, infrastructure requirements are rapidly changing. Success is increasingly determined not only by compute performance, but by how efficiently organizations can manage data, memory, context and compute resources as a unified system.
Crucial to this unified approach is VAST’s inherently versatile Disaggregated Shared Everything (DASE) architecture, which extends beyond standard storage to deliver robust multi-tenancy support for secure workload isolation, native multi-protocol access, and a unified global namespace that simplifies data access across distributed environments. By streamlining critical data operations like rapid model loading alongside VAST’s core data platform values, the system allows AI clouds to run massive, concurrent workloads while maximizing hardware utilization.
Many of today’s AI environments were designed for training-centric workflows yet struggle to support the expanding persistent context of retrieval augmented generation (RAG) pipelines and long-thinking, multi-turn inferencing. As a result, many organizations face rising infrastructure and token costs, underutilized GPUs and increasing operational complexity as they scale AI into real-world applications.
To address these challenges, VAST and AMD are expanding their collaboration to deliver an open and flexible approach to AI infrastructure that combines accelerated computing, intelligent data services and optimized inference software into a unified platform for AI clouds and enterprise AI deployments.
The collaboration includes:
- VAST has selected 6th Gen AMD EPYC processors, formerly codenamed “Venice,” to power the 6th-generation of CBox and 3rd-generation of EBox platforms to underpin the VAST AI OS. 6th Gen EPYC CPUs bring support for PCIe Gen-6 that enables 2X the I/O bandwidth generationally for improved file and object storage performance, and helps improves CPU core performance by lowering latency for critical AI data services including database, data warehouse, and event streaming via VAST’s DataBase and DataEngine capabilities.
- An AI Infrastructure Reference Architecture developed by VAST, AMD and DriveNets that features AMD Helios rack-scale AI infrastructure coupled with the VAST AI OS and DriveNets AI Fabric networking. These reference architectures document infrastructure support for model training, inference, reinforcement learning (RL) and KV cache workloads with sizing considerations and guidance for AI cloud providers and enterprises to simplify and accelerate high performance, highly available and efficient AI factory deployments.
- Expanded ecosystem collaboration with software innovators including TensorMesh and EmbeddedLLM to accelerate deployment of production-ready inference architectures optimized for agentic AI applications.
- New KV cache and inference optimizations that combine AMD Instinct GPUs, AMD Infinity Context, and AMD ROCm software with the VAST AI OS.
- Early VAST testing utilizing an AMD Instinct MI355X GPU demonstrated 9X speedup in time-to-first-token (TTFT), and 9.7X more token throughput utilizing VAST for KV Cache offloading with high concurrency agentic AI workloads.
- These accelerated and high concurrency results are critical to deliver low latency, lower cost and energy efficient inference deployments.
- Note on baselines: Because speedups are always relative to the underlying hardware, running these workloads on a GPU baseline with lower compute capacity may yield an even higher relative speedup compared to the latency of reading directly from storage.
 
- Automated KV Cache Lifecycle Management: Purging cached data that contains sensitive or personal information is a critical enterprise compliance challenge. The integration leverages VAST’s native data lifecycle policies to automatically expire and delete KV cache data, helping ensure robust security, privacy, and regulatory compliance capabilities without manual operational overhead.
- The AMD Pensando Pollara 400 AI NIC provides the high-performance data path connecting AMD Instinct GPUs to the VAST AI OS. Using NFS over TCP and NFS over RDMA, this integration efficiently moves data from GPU memory to the NVMe SSD-based VAST storage cluster, enabling the KV-cache and storage access that large-scale inference and agentic AI workloads depend on.
- Proven deployments across leading AI cloud providers delivering AMD technology-powered AI services to customers around the world.
“AI is entering an operational phase where infrastructure efficiency matters as much as model performance,” said John Mao, Vice President, Global Technology Alliances at VAST Data. “The industry is discovering that inference is fundamentally a data problem. Success depends on how effectively organizations can bring data, compute, memory and intelligence together as a single system. The VAST AI Operating System was built for this transition, giving AI cloud providers and enterprises a more efficient, scalable and open foundation for training, inference and the next generation of agentic AI applications.”
The VAST AI Operating System serves as the data and execution layer for these environments, enabling organizations to unify storage, database, streaming and AI services within a single software platform. By treating model management as a core data service, VAST virtually eliminates cold-start bottlenecks with near-instantaneous model loading that maximizes GPU utilization. Combined with AMD accelerated computing, customers can deploy scalable infrastructure capable of supporting training, inference, retrieval-augmented generation and agentic AI workloads across distributed environments.
About VAST Data
VAST Data is the AI Operating System company – powering the next generation of intelligent systems with a unified software infrastructure stack that was purpose-built to unlock the full potential of AI. The VAST AI OS consolidates foundational data and compute services and agentic execution into one scalable platform, enabling organizations to deploy and facilitate communication between AI agents, reason over real-time data, and automate complex workflows at global scale. Built on VAST’s breakthrough DASE architecture – the world’s first true parallel distributed system architecture that eliminates tradeoffs between performance, scale, simplicity, and resilience – VAST has transformed its modern infrastructure into a global fabric for reasoning AI.
Source: VAST Data
```



document fetched 2026-07-25 07:57 · canonical https://hpcwire.com/off-the-wire/vast-data-expands-collaboration-with-amd-to-advance-ai-infrastructure-for-the-inference-era