When you deploy these HFS solutions, you can specify the requirements for your file system, including:
As you specify these parameters, the HFS Marketplace solution then applies default parameters to reduce customer complexity and shorten time to deployment. For example, when building a scratch filesystem, it will select local NVMe storage. Similarly, for mixed or small file workloads it will customize metadata. File systems can be up and running in under 15 minutes.
For users who require maximum configurability for complex deployment, we also offer Oracle Cloud Marketplace Stacks (Web based GUI) and Terraform-based Oracle quickstart deployment templates on Github. Simply customize the terraform templates or Marketplace stacks to meet your requirements and launch through Resource Manager.
Built on Oracle Cloud Infrastructure, these shared file storage solutions provide high throughput and consistent, low latency, supporting high performance workloads.
Achieve file throughput of up to 500 GB/s aggregate throughput with attached HPC bare metal compute instances with local NVMe and 100 Gbps cluster networking for low latency.
Get up and running quickly and easily, with just a few clicks to deploy standard configurations.
The all-in-one solutions based on Terraform scripts include everything you need to get POSIX -compliant Lustre, GlusterFS, or BeeGFS up and running quickly and easily.
On-premises file server clusters require large capital investments, while Oracle Cloud can scale elastically to meet storage and performance needs up to 500 GB per second.
Oracle’s preconfigured environments are useful in many industries across a wide range of applications, including:
HFS solution can be used to build a POSIX file system which is accessible from on-premises compute nodes using file system native clients, NFSv3/NFSv4 or SMB to migrate data to Oracle cloud.
HPC workloads for crash simulations, Computational Fluid Dynamics (CFD), computational chemistry require massive amounts of training data and often use shared file storage to support processing datasets concurrently.
Datasets for AI and ML workloads are large, and file storage must supply massive amounts of data very quickly for training, and validation across multiple models simultaneously.
Media data processing workflows, like video rendering, visual effects, and media production, need the compute and storage resources to handle the creation of massive amounts of video files from large resource data sets.
Big data analytics use cases, including fraud detection and financial analysis, produce massive volumes of data that need high-performance storage to power data-intensive applications.
“Oracle Cloud is the only major cloud provider delivering Spectrum Scale in a shared-storage architecture on bare-metal hardware. The Oracle offering has been tuned for the demands of HPC and big-data analytics and offers 10X performance advantage over virtualized cloud offerings, improved flexibility, scalability, and manageability.”
Michael Sedlmayer, President, Re-Store
“My team has tested SAS Grid on many public clouds. We are happy to say that Oracle Cloud’s infrastructure was able to provide the I/O throughput to the IBM Spectrum Scale shared file system that is needed for SAS Grid.”
Margaret Crevar, Sr Manager, SAS Performance Lab, SAS
“The OCI HPC File system (HFS) graphical interface and its file system provisioning workflow, designed to be customer use case centric (scratch or persistent space, large, mixed or small file workloads, etc.) versus technology centric, reduces barriers to quickly deploy a parallel filesystem like BeeGFS on Oracle Cloud. Oracle Cloud offers infrastructure resources like 100Gbps RDMA RoCEv2 Clustered Network, Multi-attach Shared Block Volume service, local NVMe SSDs attached to Compute & Bare metal Compute shapes to deploy BeeGFS in many different configurations and deliver triple digit Giga-Byte throughput (500 GB/s) at lower price point compared to other public clouds”
Howard Weiss, Founder and Managing Director, Pacific Teck
“Oracle's bare metal compute and clustered networking technology allowed BeeGFS on Oracle Cloud to outperform on-premise HPC file system performance (latency & IO throughput) for MPAS workload at a very low price point. Using Oracle Cloud's Cluster Network RDMA network, BeeGFS can see performance of up to 140 GB/s with as little as 14 servers.”
Simon Ponsford, CTO, YellowDog
“The OCI parallel file system solution of BeeGFS using 100 Gbps RoCEv2 and local NVMe storage achieved similar or better IO write throughput performance compared to Lustre-based NVMe storage on a traditional DiRAC HPC system for the SWIFT cosmological application benchmark depending on the file type written. For 370 GB snapshot files, OCI achieved 6.2 GB/s and Lustre 7.0 GB/s and for 994 GB restart files OCI achieved 70 GB/s and Lustre 29.2 GB/s.”
Andrew Turner, DiRAC Technical Manager, EPCC, The University of Edinburgh
|Features||BeeGFS||GlusterFS||IBM Spectrum Scale||Lustre|
|License Type||Open Source & Commercially licensed for Enterprise features||Open Source||Commercially licensed||Open Source|
|Scalable - Storage & Performance||Yes||Yes||Yes||Yes|
|Storage Tiering||Yes*||No, experimental||Yes||Yes|
|NFS Version||v4||v3, v4||v3, v4||v3, v4|
|Server Message Block (SMB)||Yes||Yes||Yes||No|
|RDMA Support||Yes||No||Yes, Erasure Edition||No|
|Filesystem Support||SI & Community||Community||SI||SI & Community|
|Deployment||HFS, Oracle Quickstart||HFS, Oracle Quickstart||Oracle Quickstart||HFS, Oracle Quickstart|
* - Enterprise feature, available in commercially licensed software. Open Source edition include all enterprise feature to evaluate them for free for non-production use.
SI – stands for System Integrator
Pinkesh Valdria, Principal Solutions Architect
Oracle Cloud Infrastructure was recently ranked the 7th-fastest performer on the IO500, a widely recognized high-performance storage IO benchmark. The vast majority of other systems on the list are specialized on-premises environments, including research supercomputers. We achieved 500 GB/s write IO throughput and 13.1 million IOPS in metadata performance with a high-performance parallel file system using 270 nodes in an HPC cluster network running the BeeGFS BeeOND file system.Read the complete post
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