package bechamel

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Analyze module.

Micro-benchmark usually uses a linear-regression to estimates the execution time of a code segments. For example, the following table might represent {!Measurement_raw.t} array collected by

  | run | time |
  | 1   | 19   |
  | 2   | 25   |
  | 3   | 37   |
  | 4   | 47   |
  | 5   | 56   |

Bechamel records 3000 samples and the number of iterations can grows geometrically (see Then, Bechamel can use 2 algorithms:

  • Ordinary Least Square
  • RANdom SAmple Consensus

The user can choose one of it. Currently, OLS is the best to use. These algorithms will estimate the actual execution time of the code segment. Using OLS with the above data would yield an estimated execution time of 9.6 nanoseconds with a goodness of fit () of 0.992.

More generally, Bechamel lets the user choose the predictors and responder. Indeed, the user can use others metrics (such as perf) and the API allows to analyze such metrics together.

module OLS : sig ... end
module RANSAC : sig ... end
type 'a t

Type of analysis.

val ols : r_square:bool -> bootstrap:int -> predictors:string array -> OLS.t t

ols ~r_square ~bootstrap ~predictors is an Ordinary Least Square analysis on predictors. It calculates if r_square = true. bootstrap defines how many times Bechamel tries to resample measurements.

val ransac : filter_outliers:bool -> predictor:string -> RANSAC.t t
val one : 'a t -> Measure.witness -> Benchmark.t -> 'a

one analysis measure { Benchmark.stat; lr; kde; } estimates the actual given measure for one predictor. So, one analysis time { Benchmark.stat; lr; kde; } wants to estimate actual run-time (or execution time) value, where analysis is initialized with run predictor.

val all : 'a t -> Measure.witness -> (string, Benchmark.t) Stdlib.Hashtbl.t -> (string, 'a) Stdlib.Hashtbl.t

all analysis measure tbl is an application of one for all results from the given tbl.

val merge : 'a t -> Measure.witness list -> (string, 'a) Stdlib.Hashtbl.t list -> (string, (string, 'a) Stdlib.Hashtbl.t) Stdlib.Hashtbl.t

merge witnesses tbls returns a dictionary where the key is the label of a measure (from the given witnesses) and the value is the result of this specific measure.


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