When designing a storage infrastructure for an artificial intelligence (AI) or deep learning (DL) workload, the default assumption is that an all-flash array (AFA) or something even faster must be at the heart of the design. The problem is as…
Blog Archives
Are All-Flash Arrays All Wrong for AI and DL Workloads?
Tagged with: AFA, AI, All-Flash, Artificial Intelligence, Deep Learning, DL, Flash, Metadata, Object Storage, SwiftStack
Posted in Blog
Posted in Blog
Lightboard Video: The Art of Big and Fast Data
Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) projects can all have varying types of data associated with them. Some projects consist of a relatively small number of huge files, and others have an incredibly high number of…
Tagged with: AI, Analytics, Artificial Intelligence, Big data, Deep Learning, DL, IoT, Machine Learning, Memory, MemVerge, ML
Posted in Video
Posted in Video
Is Your Storage Ready for the Data-Driven Economy? – SwiftStack Briefing Note
Organizations need to re-think their storage architectures for the data-driven economy. How an organization captures, stores, and analyzes data, can dictate how successful it might be in this new economic model where data drives organizations. The data-driven economy is not…
Tagged with: AI, Artificial Intelligence, AS, Cloud, Container, Deep Learning, DL, Flash, Hard disk drive, Retention, Scale, SwiftStack, Unstructured data
Posted in Briefing Note
Posted in Briefing Note
Is Your Storage Architecture Ready for the Coming AI Wave?
Artificial Intelligence (AI) is a broad term that can apply to various computing tasks, including machine learning, deep learning, and big data analytics. Many AI projects are in a proof of concept stage, but CIOs and IT Managers need to…
Developing an NVMe over Fibre Channel Strategy
Most All-Flash Arrays (AFA) are setup as block devices connected via a Fibre Channel (FC) Storage Area Network (SAN). The deterministic nature of FC and its inherent low latency are an ideal match for AFAs. As data centers begin to…
SwiftStack for AI, ML and DL
How to Build a Multi-Cloud Data Pipeline for AI, ML and DL Artificial intelligence (AI), machine learning (ML) and deep learning (DL) are experiencing rapid adoption in a number of use cases, including autonomous vehicles, pharmaceutical drug research, predictive maintenance,…
Tagged with: AI, Artificial Intelligence, Cloud, Deep Learning, DL, HDD, Hybrid, Machine Learning, Metadata, ML, NFS, Object Storage, SMB, Software Defined, SwiftStack
Posted in Briefing Note
Posted in Briefing Note
Making HPC Available to the Masses – Dell Technologies HPC Briefing Note
With businesses beginning to rely on analytics, machine and deep learning (ML and DL), and artificial intelligence (AI) to run daily processes and generate competitive advantage, high-performance computing (HPC) is becoming more applicable outside of its traditional niche use cases,…
New eBook: Do AI and High Velocity Analytics Require a New File System?
Even though the workloads are only a few years old, the typical file system used in AI and High Velocity Analytics was created decades ago. These file systems, while parallel in nature, were optimized for large file, high bandwidth environments,…
New eBook – Selecting a File System for AI and High-Velocity Analytics Workloads
As Artificial Intelligence, Machine Learning and Deep Learning workloads go mainstream, organizations are struggling with how to develop a storage infrastructure to best meet the unique challenges of these workloads. AI/ML workloads typically include hundreds, if not thousands of servers…
WekaIO for AI and High-Velocity Analytics
Storage Switzerland has previously discussed the problems that legacy storage file systems have when it comes to serving modern workloads such as artificial intelligence (AI) and high-velocity analytics. We have also explored the qualities that a modern file system requires.…
