Failing to pick and integrate the right cloud configuration for computational heavy workloads will lead to overspending (80% in some cases) and a huge waste of time.
Not only distributed computations themselves require thought-through architecture to perform well (do you really need RDMA? what storage to pick to match your workload profile? etc.), but Cloud IaaS perform in unpredictable way depending on many hidden factors, so relying on price per core*hour to estimate your budget does not cut it, not even close.
We are a team of engineers with experience in applied math, HPC, virtualization and Cloud architecture. We did many simulations ourselves and for our customers, and we feel like we know quite a bit about how to pick the right configuration, which best fits the workload, and automate its set up.
Now we'd like to share our expertise in a form of SaaS tools available to everyone - we are at a semi-automatic stage now, so we would love to talk about your unique case as it helps us to see the whole picture.
We systematically benchmark all clouds, launching hundreds of simulations simultaneously and provide you access to conclusions and tools to do the same yourself.
Please do not hesitate, shoot us a message with any question or problem you might have. We'll be happy to help. Eugene