package core_bench

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Each Analysis_config.t specifies a regression run by Core_bench. This module also provides several typical regressions that one might want to run.

type t
val create : responder:Variable.t -> predictors:Variable.t list -> ?bootstrap_trials:int -> ?r_square:bool -> ?regression_name:string -> unit -> t
val with_error_estimation : ?bootstrap_trials:int -> t -> t

For any analysis t, return a new t that includes error estimation

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 cycles_vs_runs : t

cycles_vs_runs predicts cycles using runs.

val nanos : predictors:Variable.t list -> t

nanos ~predictors estimates nanos using specified predictors.

val cycles : predictors:Variable.t list -> t

similar to nanos

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.