Hammerspace Empowers GPU Computing With Enhanced S3 Data Orchestration

Hammerspace Tackles the Challenges of GPU Computing

Hammerspace, a pioneer in data orchestration, recently announced a significant advancement in its Global Data Platform during the 56th IT Press Tour. With the addition of the S3 interface, Hammerspace now enables S3 applications to seamlessly connect and leverage its automated data orchestration capabilities. This enhancement allows object data to be efficiently orchestrated to GPU resources alongside existing file data, unlocking new possibilities for organizations looking to optimize their data management and accelerate innovation.

According to Hammerspace Founder and CEO David Flynn, enterprises face major challenges when adopting GPU computing for AI, machine learning, and data analytics. One of the biggest hurdles is accessing available GPUs, whether in an organization's own data centers or in the cloud. An even greater challenge lies in identifying relevant data sets and placing that data in proximity to the compute resources.

"HPC centers and enterprise IT architects urgently need solutions to organize and mobilize large data sets to where GPUs are located," said Flynn. "Traditional data management approaches often result in data silos, making it difficult to efficiently move data across different storage types and locations."

Combining Parallel File System Performance With Automated Orchestration

Hammerspace addresses these challenges by combining the performance of a parallel file system with the flexibility of automated data orchestration. The addition of S3 support enables organizations to quickly organize and mobilize large data sets, regardless of location, to GPU resources.

Key benefits of Hammerspace's S3 integration include:

1. Seamless data ingestion from existing S3 data into Hammerspace's global file system
2. Optimized data pipeline across any storage type by intelligently moving data from silos to compute resources
3. Automated, metadata-driven data placement that dynamically moves and caches data based on access patterns
4. Unified namespace allowing seamless access to storage across sites and clouds as a single logical entity
5. Standards-based interoperability with pNFS, NFS, SMB, NVIDIA GPUDirect, and now S3 without needing client software

"Accessing available GPUs in an organization's own data centers or in the cloud is a challenge. Even more difficult can be identifying useful data sets and placing that data local to the available compute resources," said Molly Presley, SVP of Global Marketing at Hammerspace. "With the addition of the S3 interface, HPC centers and enterprise infrastructure architects can quickly organize and mobilize large data sets to where GPUs are located."

Breaking Down Data Silos To Accelerate AI and Analytics

The Hammerspace platform empowers AI and analytics initiatives by breaking down data silos and ensuring stakeholders have access to the latest data. Extreme parallel performance and the ability to orchestrate data to any location and storage system make it invaluable for accelerating AI workflows.

Hammerspace's data orchestration layer uses fixed logic, inheritance through directory hierarchies, and user-defined tags to automatically move files based on customizable objectives around performance, reliability, governance, and data placement. An automated optimizer handles over-provisioned or over-subscribed resources. This declarative model, unique to Hammerspace, provides unprecedented flexibility and automation.

"This is really the opportunity, to define the framework and language within which people will describe and systems will automate data orchestration across diverse infrastructure," said Flynn. "It's about changing how data exists — it's no longer emergent from storage and copied across systems."

Flexible Orchestration for Developers and IT 

For developers, Hammerspace's Hammer Script language enables writing custom data orchestration objectives. A management GUI provides visibility into data locations, objective status, and resource utilization to aid governance and compliance.

Use cases powered by Hammerspace span edge AI with disconnected operations, automated movement of data to cloud GPUs, and emerging AI Factory architectures requiring a unified data platform.

"As you think about this evolving AI Factory market, the data platform it runs on needs access to all data sources," said Presley. "If we isolated out S3, you'd be missing some data sources and wouldn't have a holistic view of your data environment to accomplish your AI training with confidence."

By integrating S3 support into its Global Data Platform, Hammerspace has taken a major leap forward in empowering enterprises to fully leverage their data assets across edge, data center, and cloud environments. The ability to automatically orchestrate object data alongside file data unlocks opportunities to accelerate innovation through GPU computing and advanced analytics.