asymptoticMemoryUsage: Asymptotic Memory Metrics Quantifying function

In Anirban166/testComplexity: Asymptotic Complexity Testing Framework

Asymptotic Memory Metrics Quantifying function

Description

Function to compute benchmarked memory allocation with different data sizes for an R expression

Usage

asymptoticMemoryUsage(e, data.sizes, max.bytes)

Arguments

e	An expression which is in the form of a function operating on 'N' (as the data size for the algorithm to be tested against for a run), which takes values from the used-supplied parameter data.sizes.
data.sizes	A vector/set of data sizes, which should preferably be a sequence in powers of ten, with mid-values included. Example: data.sizes = 10^seq(1, 4, by = 0.1)
max.bytes	The maximum number of allocated bytes an iteration would be limited upto for the passed expression. (once the limit has been exceeded, further computations on incrementally larger dataset sizes won't be done) Optional, with default value set to 10^6 bytes. (1 Megabyte/MB)

Details

For more information regarding its implementation or functionality/usage, please check https://anirban166.github.io//Memory-usage-quantifier/

Value

A data frame comprising of the memory usage (in megabytes) computed by bench and the corresponding dataset sizes.

Examples

# Memory profiling must be available in the running system:
if(capabilities("profmem")) {
# Quantifying the memory usage for the allocation of a square matrix (N*N dimensions)
# against a set of input data sizes:
input.sizes = 10^seq(1, 3, by = 0.1)
asymptoticMemoryUsage(matrix(data = N:N, nrow = N, ncol = N), input.sizes)
}

Anirban166/testComplexity documentation built on April 21, 2023, 6:15 p.m.