Scala Computing careers

We built a software product that minimizes network latency by applying spectral graph theory and proprietary heuristics to optimize the distribution of workloads by Job Schedulers within dynamic computing environments of large-scale parallel systems, decreasing time-to-results and increasing aggregate machine utilization for some of the world's most important applications including real-time medical imaging, energy research, weather forecasting, and machine learning.

Our software is job scheduler agnostic and optimally allocates hardware or Virtual Machines for a given workload to minimize network (port-to- port) latency. The product has consistently demonstrated network latency decreases of over 60% on Public Cloud environments such as Amazon Web Services and has been tested with industry standard benchmarks in the MPI Test suite.