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Description
The convergence of high-performance computing (HPC) and machine learning is placing unprecedented requirements on storage solutions, as the input/output demands of these two distinct workloads diverge significantly. This shift is occurring at this very moment, with a recent analysis from the independent firm Intersect360 revealing that a striking 63% of current HPC users are actively implementing machine learning applications. Furthermore, Hyperion Research projects that, if trends continue, public sector organizations and enterprises will see HPC storage expenditures increase at a rate 57% faster than HPC compute investments over the next three years. Reflecting on this, Seymour Cray famously stated, "Anyone can build a fast CPU; the trick is to build a fast system." In the realm of HPC and AI, while creating fast file storage may seem straightforward, the true challenge lies in developing a storage system that is not only quick but also economically viable and capable of scaling effectively. We accomplish this by integrating top-tier parallel file systems into HPE's parallel storage solutions, ensuring that cost efficiency is a fundamental aspect of our approach. This strategy not only meets the current demands of users but also positions us well for future growth.
Description
High-performance tasks associated with data-heavy AI, IoT, and HPC workloads have traditionally relied on costly, top-tier processors or accelerators like Graphics Processing Units (GPUs) to function optimally. Additionally, organizations utilizing cloud-based platforms for demanding computational tasks frequently encounter trade-offs that can be less than ideal. For instance, the outdated nature of processors and hardware in cloud infrastructures often fails to align with the latest software applications, while also raising concerns over excessive energy consumption and environmental implications. Furthermore, users often find certain features of cloud services to be cumbersome and challenging, which hampers their ability to create tailored cloud solutions that meet specific business requirements. This difficulty in achieving a perfect balance can lead to complications in identifying appropriate billing structures and obtaining adequate support for their unique needs. Ultimately, these issues highlight the pressing need for more adaptable and efficient cloud solutions in today's technology landscape.
API Access
Has API
API Access
Has API
Integrations
Automai Robotic Process Automation
Check Point IPS
Check Point Infinity
SQLXPress
XYGATE Identity Connector
XYGATE SecurityOne
Integrations
Automai Robotic Process Automation
Check Point IPS
Check Point Infinity
SQLXPress
XYGATE Identity Connector
XYGATE SecurityOne
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
Hewlett Packard
Founded
2015
Country
United States
Website
www.hpe.com/us/en/solutions/hpc-high-performance-computing/storage.html
Vendor Details
Company Name
ScaleMatrix
Founded
2011
Country
United States
Website
www.scalematrix.com/scalecloud
Product Features
Product Features
Cloud Management
Access Control
Billing & Provisioning
Capacity Analytics
Cost Management
Demand Monitoring
Multi-Cloud Management
Performance Analytics
SLA Management
Supply Monitoring
Workflow Approval
