In my mind "cloud" is the next logical evolution of computing - better resource management through enabling applications to better communicate with their supporting infrastructures (servers, storage, network, cpu and memory resources) to allow applications to have the intelligence to scale up and down based on demand. "Cloud Computing" also has a valid connection to outsourcing in the sense that shared infrastructures will at some point over take privately managed information technology (IT) infrastrucures that are common today.
There are several points about the above listed whitepaper from UnivaUD that caught my attention:
- MPI was only mentioned once. The Message Passing Interface (MPI) is the standard on which most HPC applications and platforms are built. For a paper to truly look at the potential of outsourcing HPC to a "cloud" environment, an indepth review of MPI will need to be done to ensure the proper updates are made to handle the additional physical layer errors that could occur in a shared environment, as well as the added challenges of communication in an unknown environment.
- There was very little mention of the actual applications that are common in HPC. Applications like Fluent, NAMD, NWChem, Gaussian, and FFTW are commonly used on clusters built in house to meet the specific needs of a given community. Moving those applications from these small, in-house envirronments will take time and review to ensure they are able to scale in shared environments, as well as properly handle the increased variation possible in hardware and configurations.
- There was no mention of parallel file systems. This is a fundamental requirement of modern HPC environments. To truly move common HPC environments into the "cloud" a solution will be needed for data management and transfer at the high speeds required of todays applications.
As time allows I hope to explore the above issues, particularly looking at alternatives for parallel file systems in environments that may have varying latency, and are distributed over various data centers.