# Pascal Compute

Source: https://www.trypascal.io/platform/compute

Run the calculation. Keep the context.

Run analytical and computational jobs with defined inputs, resources, and outputs. Trace each result to the code, environment, and logs behind it.

## Capabilities

### Define a reproducible job

Package the code, dependencies, configuration, and expected outputs needed to repeat a computational task.

### Bring governed inputs

Bind the datasets, documents, and model artifacts the job needs. Keep the input selection connected to its origin and access scope.

### Choose the required resources

Declare the environment and capacity needed for the workload, then use an approved execution path that can satisfy them.

### Check the run before it starts

Validate the job configuration and available capacity. Inspect applicable limits and cost information before execution.

### Follow progress and failure

Inspect the run’s state, logs, and intermediate work. Distinguish queued, running, failed, and completed jobs.

### Keep useful results durable

Collect outputs with the run that produced them. Reuse those artifacts in model development, analysis, or the next operational step.

## Connected context

Use datasets and files as inputs, coordinate jobs with Workflows, and carry outputs into analysis, model development, or Atlas scenarios. Keep the job connected to the decision it supports.

- Job definitions, environment versions, and workload profiles
- Input files, resource limits, network rules, and checkpoints
- Logs, usage, cost information, and saved outputs

## Controls and permissions

A job needs an available environment, capacity, and permission to run. Completion confirms the computation, while its output still needs to be assessed for the intended use. Any resulting business action requires its own authorization.

## Example

A carrier recovery needs a capacity calculation. The team opens the optimizer job from its Task, inspects the execution details, and reads the retained logs. The calculation supports the recovery decision, and the operator remains responsible for approving any carrier change.

## Workflow

### Open the job from the work

- The recovery Task retains the optimizer result. Follow its link to the completed job rather than reconstructing the computation elsewhere.

### Inspect the execution details

- Review the Python runtime, machine resources, timing, and completion status associated with this run.

### Read the result with its context

- The retained logs describe the input and candidate capacity. The team can use that evidence in a routing decision; computation itself does not change a carrier booking.

## Next steps

Bring the workload, its inputs, the resources it needs, and the output your team will use to decide what happens next.

- [Contact sales](https://www.trypascal.io/contact)
- [Pascal Work](https://www.trypascal.io/solutions/pascal-work)