The rapid adoption of artificial intelligence and machine learning systems in every industry has created an unprecedented scaling challenge as businesses convert data from knowledge into intelligence. These advanced use cases can be solved now with composable infrastructure where storage, compute, and networking resources are abstracted from their physical locations and are orchestrated by software that optimizes available hardware resources. Volumez makes AI/ML data services composable, scalable, and universal across the public and private cloud, keeping GPU pipelines fed with data and preventing noisy neighbors from impacting other workloads in complex MLOps environments.
vs shared file system
Train larger models in less time with Volumez Direct File architecture. Volumez delivers 160GB/sec of guaranteed bandwidth to each GPU server, enabling AI engineers and MLOps to deliver better, faster business insights.
Eliminate the shared storage I/O bottleneck that limits the scale of today’s AI/ML training cycles. Volumez controller-less architecture independently connects each GPU directly to raw NVMe media, eliminating noisy neighbors and the scalability limits of storage controllers, metadata servers, and cluster locks.
Lower GPU hardware costs while increasing training cycle performance. Volumez eliminates idle time imposed on GPU servers due to I/O bottlenecks, improving time to insights and reducing total cost of training.