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Parallel Job Speedup Calculator

Work out parallel job speedup instantly with clear inputs, formula shown and shareable results.

About Parallel Job Speedup Calculator

Splitting work across jobs is bounded by Amdahl's law and by per-job overhead. The unparallelisable fraction sets a floor, and every extra job adds its own setup cost, so wall clock is U-shaped in job count. The optimum is roughly the square root of splittable work divided by per-job overhead, beyond which adding runners makes the pipeline slower.

Formula

Parallel wall clock

wall clock = fixed work + splittable / jobs + per-job overhead; optimal jobs ~ sqrt(splittable / overhead)

Worked example

With the default values below, Parallel Job Speedup Calculator returns Wall-clock duration of 386. Change any input above and every figure here is recalculated in your browser.

Inputs used

Total serial workminimum 1 s
1,800 s
Parallel jobsaccepts 1–512
8
Fixed overhead per jobminimum 0 s
35 s
Work that cannot be parallelisedaccepts 0–100 %
8 %

Results

Wall-clock duration
386 s
Speedup versus serial
4.66 x
Parallel efficiency
58.3%
Job count that minimises wall clock
7

Step by step

  1. 1Values used
  2. 2Parallel wall clock
  3. 3Wall-clock duration= 386 s
  4. 4Speedup versus serial= 4.66 x
  5. 5Parallel efficiency= 58.3
  6. 6Job count that minimises wall clock= 7

Assumptions and limits

  • The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
  • In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
  • Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

Why does adding jobs eventually slow things down?

Each job pays checkout, dependency install and container startup. Once that overhead exceeds the work it removes from the critical path, total time rises.

How should tests be split across jobs?

By recorded historical duration rather than by file count. Alphabetical or count-based splits leave some jobs idle while one runs the slow suite.

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