High-performance clusters bring many advantages to the end user, including flexibility and efficiency. With the increasing number of applications being served by high-performance systems, new systems need to serve multiple users and applications. Traditional high-performance systems typically served a single application at a given time, but to maintain maximum flexibility a new concept of “HPC as a Service” (HPCaaS) has been developed. HPCaaS includes the capability of using clustered servers and storage as resource pools, a web interface for users to submit their job requests, and a smart scheduling mechanism that can schedule multiple different applications simultaneously on a given cluster taking into consideration the different application characteristics for maximum overall productivity.
HPC as a Service enables greater system flexibility since it eliminates the need for dedicated hardware resources per application and allows dynamic allocation of resources per given task while maximizing productivity. It is also the key component in bringing high-performance computing into cloud computing. Effective HPCaaS though, needs to take into consideration the application’s demands and provide the minimum hardware resources required per application. The scheduling of runs of multiple applications at once requires the proper balance of resources for each application proportional to their demands.
Research activities on HPCaaS are being performed at the HPC Advisory Council (http://hpcadvisorycouncil.mellanox.com/). The results show the need for high-performance interconnects, such as 40Gb/s InfiniBand, to maintain high productivity levels. It was also shown that scheduling mechanisms can be set to guarantee same levels of productivity in HPCaaS versus the “native” dedicated hardware approach. HPCaaS is not only critical for the way we will perform high-performance computing in the future, but as more HPC elements are brought into the data center, it will become an important factor when building the most efficient enterprise data centers.
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