Future Trends in HPC, part 2

Future Trends for High Performance Computing Image

This is a continuation of our look at future trends in high performance computing. In part 1 we covered the first five of the top ten trends. In this installment we’ll wrap up with the remaining five.

Continue reading

GPU workstation sale (and other news)

Image of Supermicro workstationWow, this is the first update in a while on the ICC blog. We have been working on several web-based projects that have been keeping us busy, and I would like to highlight some of them (and other news) in this post.

Website and product news

First of all, as you may have noticed, our HPC by ICC section of the site launched earlier this month which describes ICC solutions for high-performance computing clusters. There is an outline of the Platform Computing HPC Suite, an industry-leading cluster management software package, as well as a diagram which explains common cluster components. Our goal is to open up high-performance computing to industries that have been slow to adopt it, even though HPC may save them a lot of money in the long term and help them stay competitive. If you think you could benefit from an upgrade to your IT infrastructure, feel free to contact us for a free consultation.

At SC10, Supermicro unveiled their GPU SuperBlade server modules (SBI-7126TG) that will offer perhaps the highest density CPU-GPU computing power available on the market. A 42U rack, comprised of six 7U blade enclosures – each with ten GPU SuperBlade modules – can carry 120 CPUs and 120 GPUs. For comparison, a rack with 42 standard dual-processor 1U servers would have 84 CPUs and no GPUs. We will have these high-density server products available on our site soon after they are released. Read more about them in the Supermicro press release or on this podcast interview with Tau Leng, GM of Supermicro, by insideHPC.

Continue reading

HPC and the life sciences

Connected network cablesThis 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 maximizing accessibility to 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 to accommodate 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.