Compute-Intensive Workloads in the Cloud
Easy. Fast. Secure.
Easy and fast deployment of compute-intensive apps’ dataKmesh SaaS reduces your data planning and provisioning time by up to 90 percent. No more moving data around data centers or cloud locations. Simply establish data orchestration policies and your HPC apps can access the right data at the right time.
Use Cases: Compute-Intensive Workloads
High performance computing (HPC)Scientists and engineers use HPC to solve complex, compute-intensive problems, such as genomics. They can process massive amounts of data that need to be accessed by multiple compute instances with high levels of throughput. Kmesh lets you distribute file system data for optimal performance of short-lived, compute-intensive workloads, with file system access across all locations.
Cloud bursting from on-premisesOn-premises, compute-intensive workloads frequently need extra compute and storage capacity to handle peaks in demand. Kmesh lets you burst on-premises, compute-intensive workloads to cloud by transferring data seamlessly.
Big data analyticsFraud detection, seismic processing, genomics, and more require data-intensive applications. Kmesh Lustre-as-a-Service provides the performance for faster analytics and value.
Machine learningMachine learning workloads use massive amounts of training data. These workloads often use shared file storage because multiple compute instances need to process the training datasets concurrently. Kmesh provides an efficient way to achieve massively parallel shared file storage with high throughput and consistent, low latencies to process your ML training datasets.
Electronic Design Automation (EDA)EDA is used to simulate performance and failures during the design phase of silicon chip production. These compute-intensive workloads can lead to either over-provisioning and high costs or under-provisioning and capacity restrictions. Kmesh Lustre-as-a-Service provides the performance and flexibility you need to innovate faster, design and verify new products, and scale to meet demand.
Media processing and transcodingMedia data processing workflows, like video rendering, visual effects, and media production, need the compute and storage resources to handle the massive amounts of data being created. Kmesh Lustre-as-a-Service provides the high performance and low latencies needed for processing, distributing, and analyzing digital media files.
The Kmesh SaaS for Compute-Intensive Workloads in the Cloud
You want to distribute the compute for any complex problem across multiple CPUs to minimize execution time. Whether performing engineering simulations, financial risk analyses, molecular dynamics, or other HPC workloads, you need to rapidly exchange data for concurrent computations.
Kmesh SaaS incorporates all the functionality needed to real-time manage HPC app data across cloud, hybrid cloud, and multi-cloud deployments.
- Bursting of compute-intensive workloads to cloud without performance bottlenecks
- Seamless transfer of data between on-premises data sources and apps on public clouds
- Synchronization of data changes within on-premises sources to apps in the cloud in real time
- Intelligent cloud data caching to ‘spin up’ cloud apps faster
The Kmesh SaaS solution operates within your existing infrastructure to distribute file system data over your cloud and edge locations via a single global namespace. Simply configure your business rules / data orchestration policies through the Kmesh portal and rapidly deploy your data over any cloud location(s).
Kmesh SaaS exploits Lustre’s performance and scalability to support the stringent latency and throughput demands of the most compute-intensive apps.
Sync data from on-premises apps into less expensive storage and cloud-based clusters. You can efficiently sync results data with data from other apps, both on-premises and cloud.
Sensitive on-premises data can be accessed from public cloud without experiencing security issues, while apps can be brought up faster on cloud – without waiting for data transfer.
Since Kmesh SaaS operates within any existing cloud infrastructure and security architecture, you do not have to make changes to any of your data storage infrastructure to leverage Kmesh SaaS quickly.