parallel

Syntax: | parallel | <task> <max num of processes> |
---|

where `<task>` is currently limited to `leven`, `error`, `steppar`, `goodness`,
or `walkers`. For best results,
it is recommended that you set `<max num of processes>` to the number of CPU cores on your machine.
Set `<max num processes>` back to 1 to turn parallel processing off for the particular task.
To display current settings, type 'parallel' with no arguments.

The `leven` option will spawn up to `<max num>` processes during the Levenberg-Marquardt fitting,
specifically to perform the N independent calculations of the parameter first-order
partial derivatives (N being the number of variable fit parameters).

The speed-up that one can expect is highly dependent upon the model in use. For simpler models with quick calculation times, you will probably see little to no speed gain with parallel leven. But with multi-core CPUs, gains should be quite noticeable when the model calculation consumes a large fraction of the overall fitting time. For example, with fits using the time-intensive sedov model on a 4-core machine, we've typically seen about a 40% reduction in fit time compared with the single processing case.

The `error` option is for running parallel computations within XSPEC's error command.
This enables the error calculations for multiple parameters to be performed simultaneously.
The speed-up here should simply be proportional to the number of cores available.
However for cases where complications are reported (such as a new minimum found,
or a non-monotonicity in the statistic space), it is recommended that you perform
the error calculations in standard single-process mode.

When the `steppar` option is set, XSPEC will divide the N-dimensional steppar grid into
`<max num>` sections of equal size, and spawn a separate process for calculating each section.

If both parallel `leven` and `error` or `steppar`
are in use, XSPEC will temporarily disable the lower-level`leven`
parallelization when running the higher-level parallel `error`
or `steppar` command calculations.

The `goodness` option is for parallelizing the calculations of the
simulated spectra during a goodness command run. The `walkers`
option may be used to speed up the calculation of sets of `walkers`
needed for Monte Carlo Markov Chain runs using the Goodman-Weare algorithm
(see chain).

Examples:

XSPEC12> model cflow // Using a model with 5 variable fit parameters. XSPEC12> parallel leven 4 XSPEC12> fit // Calculations for the 5 parameters will be divided amongst // 4 processes during the fit. XSPEC12> parallel leven 1 // Restores single-process calculation to the // Levenberg-Marquardt algorithm. XSPEC12> parallel error 3 // Allow up to 3 simultaneous 'error' parameter calculations // to be performed in parallel. XSPEC12> error 2 3 6 // Perform error calculations on parameters 2, 3, and 6 in parallel. XSPEC12> parallel steppar 4 // The following 20x30 steppar grid will be split amongst // 4 parallel processes. XSPEC12> steppar 1 10. 11. 20 2 .5 .8 30 // Display current settings: XSPEC12> parallel Maximum number of parallel processes: error: 3 goodness: 1 leven: 1 steppar: 4 walkers: 1