HPC and the life sciences
This week, a team from our company visited a large laboratory located in the Chicago area. IT representatives there told us how a major focus for them has been migrating their computing resources from a model of individual workgroups using separate clusters to a shared private cloud that all research teams in the facility can access for running their jobs. This shift to private clouds for getting the most out of dedicated clusters is a hot topic of conversation in the HPC world.
HPC in the Cloud recently published an article responding to a case study written by Platform Computing about the implementation of a private cloud at the Harvard Medical School. Both are worth a read if you are interested in the challenges encountered by small- and medium-sized life sciences organizations when they try to adopt HPC clusters.
HPC holds much promise for organizations such as the Harvard Medical School. With middleware such as Platform Computing (we are biased, I must admit, since this is what HPC clusters by ICC deploy as well) it is getting easier to operate an HPC cluster with hosts running different operating systems and applications. It used to be that this multiplicity of software on the same cluster would cause extensive compatibility and usability problems, but not so much anymore. End-users in the life sciences (such as medical researchers) are benefiting from computing applications that are productive and easy to use.
So Harvard Medical School, as the HPC in the Cloud article describes, has migrated from an inefficient computing model of unshared individual computers scattered across various laboratories to a centralized private cloud that can be accessed by any of those users and managed as one unit. Simplifying maintenance while maximizingaccessibilityto HPC resources by medical school staff is most likely going to save money and increase the pace of innovation in the long run.
While this is a hopeful case study that sheds light on how other organizations can pool their computing resources to great effect, challenges remain for spreading this model to other small- and medium-size laboratories and businesses. For one, private medical companies are heavily regulated by the government and their IT infrastructure has to incorporate many time-consuming applications to store detailed records.
HPC is becoming more affordable and easier to use, but software has to continue evolving toaccommodate the particular context of each industry. Only then will the life sciences (not to mention other markets) have a truly turn-key HPC solution that can benefit labs and private companies of every size.
HPC and the life sciences
This week, a team from our company visited a large laboratory located in the Chicago area. IT representatives there told us how a major focus for them has been migrating their computing resources from a model of individual workgroups using separate clusters to a shared private cloud that all research teams in the facility can access for running their jobs. This shift to private clouds for getting the most out of dedicated clusters is a hot topic of conversation in the HPC world.
HPC in the Cloud recently published an article responding to a case study written by Platform Computing about the implementation of a private cloud at the Harvard Medical School. Both are worth a read if you are interested in the challenges encountered by small- and medium-sized life sciences organizations when they try to adopt HPC clusters.
HPC holds much promise for organizations such as the Harvard Medical School. With middleware such as Platform Computing (we are biased, I must admit, since this is what HPC clusters by ICC deploy as well) it is getting easier to operate an HPC cluster with hosts running different operating systems and applications. It used to be that this multiplicity of software on the same cluster would cause extensive compatibility and usability problems, but not so much anymore. End-users in the life sciences (such as medical researchers) are benefiting from computing applications that are productive and easy to use.
So Harvard Medical School, as the HPC in the Cloud article describes, has migrated from an inefficient computing model of unshared individual computers scattered across various laboratories to a centralized private cloud that can be accessed by any of those users and managed as one unit. Simplifying maintenance while maximizingaccessibilityto HPC resources by medical school staff is most likely going to save money and increase the pace of innovation in the long run.
While this is a hopeful case study that sheds light on how other organizations can pool their computing resources to great effect, challenges remain for spreading this model to other small- and medium-size laboratories and businesses. For one, private medical companies are heavily regulated by the government and their IT infrastructure has to incorporate many time-consuming applications to store detailed records.
HPC is becoming more affordable and easier to use, but software has to continue evolving toaccommodate the particular context of each industry. Only then will the life sciences (not to mention other markets) have a truly turn-key HPC solution that can benefit labs and private companies of every size.