Skip to content
GitLab
Explore
Sign in
Primary navigation
Search or go to…
Project
S
swiftmpistepsim
Manage
Activity
Members
Labels
Plan
Issues
Issue boards
Milestones
Wiki
Code
Merge requests
Repository
Branches
Commits
Tags
Repository graph
Compare revisions
Snippets
Build
Pipelines
Jobs
Pipeline schedules
Artifacts
Deploy
Releases
Container registry
Model registry
Operate
Environments
Monitor
Incidents
Analyze
Value stream analytics
Contributor analytics
CI/CD analytics
Repository analytics
Model experiments
Help
Help
Support
GitLab documentation
Compare GitLab plans
Community forum
Contribute to GitLab
Provide feedback
Keyboard shortcuts
?
Snippets
Groups
Projects
Show more breadcrumbs
SWIFT
swiftmpistepsim
Commits
28e48586
Commit
28e48586
authored
2 years ago
by
Peter W. Draper
Browse files
Options
Downloads
Patches
Plain Diff
Add some documentation
parent
d0454b26
No related branches found
No related tags found
1 merge request
!6
Version with faked data
Changes
1
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
README.fakedata.md
+49
-0
49 additions, 0 deletions
README.fakedata.md
with
49 additions
and
0 deletions
README.fakedata.md
0 → 100644
+
49
−
0
View file @
28e48586
swiftmpifakestepsim
===================
The swiftmpifakestepsim program works much like swiftmpistepsim, except that
it generates fake logs:
```
Usage: ./swiftmpifakestepsim [options] nr_messages logfile.dat
options: -v verbose, -d data check, -s size (bytes/scale),
-f <1|2> randomize injection order, 1 == just sends, 2 == sends and recvs
[-r uniform random from 1 to size, |
-r -g half gaussian random from 1 with 2.5 sigma size., |
-r -c <file> use cdf from file, size is a scale factor., |
-r -o <file> use occurence sample of values in a file, size is a scale factor.,]
-x random seed
```
To use a fixed message size just use
`-s`
.
To use a uniform distribution in the range 1 to N:
```
-s N -r
```
To use a half gaussian (so biased towards smaller packets) use:
```
-r -s <scale> -g
```
The cdf option reads a simple text file with a sampling of a cumulative
distribution function, where each line has three values, the minimum and
maximum range of the current bin and the value. Note that the value column
should be normalized into the range 0 to 1.
```
-r -s <scale> -c <cdf_file>
```
The occurrence file has just one value per line, these should present the
sizes of the packets, this is used to form a cdf:
```
-r -s <scale> -o <occurrence_file>
```
Other options are useful to make sure that the randoms are different,
`-x`
and
that they run in different order
`-f <1|2>`
.
Peter W. Draper 24 Apr 2023
---------------------------
This diff is collapsed.
Click to expand it.
Preview
0%
Loading
Try again
or
attach a new file
.
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Save comment
Cancel
Please
register
or
sign in
to comment