Faster hCloud experiments

Large-scale HASH simulations can generate a lot of data. Whilst hCloud made running these a breeze, subsequently streaming the results of these runs down from the cloud took a lot of time. We’re now doing two things to reduce time-to-results:

  1. We’ve made data transfer itself more performant (9-10x faster) by reconfiguring our data storage backend. This invisible change means that simulation runs and other data will download up to an order of magnitude faster.
  2. Free users of HASH were previously constrained to running cloud simulations serially. We now execute runs in parallel for all users.

We’re also releasing a third improvement, which we’ll share with you in our next update, which cuts the amount of data transfer required to view experiment results by pre-computing analysis graphs in hCloud, cutting the amount of data transfer required overall.

Process modeling library

We’ve been creating and collecting high-quality business process behaviors in a new HASH package. The Process Modeling Library to make it easy to build your own process models: representing systems or other entities which perform sequences of tasks. By chaining together processes like resource depletion, delays, and other blocks representing real-life tasks and events, you can represent processes such as assembly lines, company workflows, and supply chains.

The library is easily extensible with custom behaviors that you can write to accurately model your system. Building process models allows you to answer questions about your system. They can help you improve resource allocation, reduce cycle-time, and identify other optimizations that can be made to your organization or system. This is especially effective when used alongside HASH’s Experiments functionality to explore multiple scenarios and configurations.‌

We’ve added a section to our docs on Process Modeling with HASH that outlines how best to get started.