Each Analysis_config.t
specifies a regression run by Core_bench
. This module also
provides several typical regressions that one might want to run.
val create : responder:Variable.t ‑> predictors:Variable.t list ‑> ?bootstrap_trials:int ‑> ?r_square:bool ‑> ?regression_name:string ‑> unit ‑> t
val nanos_vs_runs : t
nanos_vs_runs
predicts nanos using runs. In this regression and all of the ones
below, no error estimate is computed.
val nanos : predictors:Variable.t list ‑> t
nanos ~predictors
estimates nanos using specified predictors
.
val allocations_vs_runs : t list
allocations_vs_runs
estimates minor allocations, major allocations and
promotoions in terms of runs and overhead.
val gc_vs_runs : t list
allocations_vs_runs
estimates minor collections, major collections and
compations in terms of runs.
val default : t list
A laundry list of several typical regressions: nanos_vs_runs
,
allocations_vs_runs
and gc_vs_runs
.