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Description
Hammerspace innovatively leverages the local NVMe storage embedded within GPU servers, converting it into a high-performance, shared storage tier designed specifically for large-scale AI training and checkpointing workloads. This approach eliminates bottlenecks inherent in legacy storage systems that struggle to keep GPUs fully utilized, while significantly reducing power consumption and external storage expenses. The platform’s parallel file system architecture supports massive scalability, allowing data to be served simultaneously to thousands of GPU nodes with minimal latency. Hammerspace integrates seamlessly with existing Linux storage servers and supports hybrid cloud environments, enabling data orchestration between on-premises and cloud infrastructure. It delivers record-setting performance validated by MLPerf benchmarks, proving its efficiency for demanding machine learning workloads. Customers such as Meta and Los Alamos National Laboratory trust Hammerspace to optimize their AI data pipelines and infrastructure investments. With quick setup and intuitive management, Hammerspace helps organizations accelerate AI projects while reducing operational complexity. By transforming underutilized storage into a powerful resource, Hammerspace drives cost savings and faster innovation.
Description
Excelero offers a low-latency distributed block storage solution tailored for web-scale applications. With NVMesh, users can access shared NVMe technology over any network while maintaining compatibility with both local and distributed file systems. The platform includes a sophisticated management layer that abstracts the underlying hardware, supports CPU offload, and facilitates the creation of logical volumes with built-in redundancy, all while providing centralized management and monitoring capabilities. This allows applications to leverage the speed, throughput, and IOPS of local NVMe devices combined with the benefits of centralized storage, all without being tied to proprietary hardware, ultimately lowering the total cost of ownership for storage. Additionally, NVMesh's distributed block layer empowers unmodified applications to tap into pooled NVMe storage resources, achieving performance levels comparable to local access. Moreover, users can dynamically create arbitrary block volumes that can be accessed by any host equipped with the NVMesh block client, enhancing flexibility and scalability in storage deployments. This innovative approach not only optimizes resource utilization but also simplifies management across diverse infrastructures.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
AutoSys Workload Automation
Azure Marketplace
DedicatedCore
Google Cloud Platform
Hadoop
Kubernetes
LawCruit
Microsoft Azure
MongoDB
Integrations
Amazon Web Services (AWS)
AutoSys Workload Automation
Azure Marketplace
DedicatedCore
Google Cloud Platform
Hadoop
Kubernetes
LawCruit
Microsoft Azure
MongoDB
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Hammerspace
Founded
2018
Country
United States
Website
hammerspace.com
Vendor Details
Company Name
Excelero
Founded
2014
Country
United States
Website
www.excelero.com/product/nvmesh/
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Disaster Recovery
Administration Policies
Bare-Metal Recovery
Encryption
Failover Testing
Flexible Data Capture
Multi-Platform Support
Multiple Data Type Support
Offline Storage
