Within today’s ever-expanding business world – there are more demands from the HPC community specifically when it comes to business intelligence and big data. Every bit of information can be quantified and that data can be used for smart business decisions or better understanding the customer base. Regardless of the use – data which traverses the modern high-performance computing platform must be controlled and even optimized.
Currently, we have a big data challenge. Intense simulations and big data analysis are now demanding new approaches to effective data quantification. These analyses processes are absolutely resource demanding and thus each application often requires many servers. In some HPC communities, truly demanding big data engines may even require thousands of servers to be dedicated to such an application. Because of their intense nature, scheduling and resource allocation become critical for these instances. Furthermore, to run these applications optimally across a compute cluster, data center, or cloud there is a required level of sophistication that is difficult to automate.
Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to interoperate easily and automatically within existing IT infrastructure.
In this whitepaper from Intersect 360 Research and Adaptive Computing – we learn about the new concept around Big Workflow and how it directly addresses the needs of critical, data-intensive, applications. By creating more intelligence around data control, Big Workflow directly provides a way for big data, HPC, and cloud environments to interoperate, and do so dynamically based on what applications are running.
You will also learn how Big Workflow can:
- Schedule, optimize and enforce policies across the data center
- Enable data-aware workflow coordination across storage and compute silos
- Integrate with external workflow automation tools
Remember, data within the cloud and the HPC world will continue to increase. As more users utilize data-intensive applications – organizations will need to find was to better control valuable data points. With Big Workflow, Adaptive Computing is offering not just a data control platform, but a true data management layer that will allow users to meet the unique workflow requirements of big data applications. Download this white paper today.