Written by: Nicole Hemsoth
Back in 2010, when the term “cloud computing” was still laden with peril and mystery for many users in enterprise and high performance computing, HPC cloud startup, Nimbix, stepped out to tackle that perceived risk for some of the most challenging, latency-sensitive applications.
At the time, there were only a handful of small companies catering to the needs of high performance computing applications and those that existed were developing clever middleware to hook into AWS infrastructure. There were a few companies offering true “HPC as a service” (distinct datacenters designed to fit such workloads that could be accessed via a web interface or APIs) but many of those have gone relatively quiet over the last couple of years.
When Nimbix got its start, the possibilities of running HPC workloads in the cloud was the subject of great debate in the academic-dominated scientific computing realm. As mentioned above, concerns about latency in the performance-conscious realm of these applications loomed large, as did the more general concerns about the cost of moving data, the remote hardware capability for running demanding jobs, and the availability of notoriously expensive licenses from HPC ISVs.
While Amazon and its competitors plugged away at the licensing problem, they were still missing the hardware and middleware specialization needed to make HPC in the cloud truly possible, even those AWS tried early on to address this by adding 10 GB Ethernet and multicore CPU options (and later, lower-end Nvidia GRID GPUs). In those early days, this difficulty is what fueled the rise of other HPC cloud startups like Cycle Computing, which made running complex jobs on AWS more seamless—but the other way to tackle the problem was simply to build both the hardware and software and wrap it neatly in a cloud operating system that could orchestrate HPC workflows with those needs in mind.