panel_model_gflops

Use the starvz Application data to observe how the regression model used
in the task anomaly classification fits the data.

Performance analysis workflow that combines the power of the R
language (and the tidyverse realm) and many auxiliary tools to
provide a consistent, flexible, extensible, fast, and versatile
framework for the performance analysis of task-based applications
that run on top of the StarPU runtime (with its MPI (Message
Passing Interface) layer for multi-node support).  Its goal is to
provide a fruitful prototypical environment to conduct performance
analysis hypothesis-checking for task-based applications that run
on heterogeneous (multi-GPU, multi-core) multi-node HPC
(High-performance computing) platforms.

Vinicius Garcia Pinto

starvz

R-Based Visualization Techniques for Task-Based Applications

Lucas Mello Schnorr

Lucas Leandro Nesi

Marcelo Cogo Miletto

Guilherme Alles

Arnaud Legrand

Luka Stanisic

Rémy Drouilhet

panel_model_gflops function

<dl><dt>data</dt>
<dd>starvz_data with trace data</dd>
<dt>freeScales</dt>
<dd>free X,Y scales for each task and resource type combination</dd>
<dt>model_type</dt>
<dd>Choose the regression model type to use</dd></dl>

Arguments

Create the diagnostig plot for the regression model — panel_model_gflops

<dl>

<dt>data</dt>
<dd>starvz_data with trace data</dd>


<dt>freeScales</dt>
<dd>free X,Y scales for each task and resource type combination</dd>


<dt>model_type</dt>
<dd>Choose the regression model type to use</dd>

</dl>

panel_model_gflops: Create the diagnostig plot for the regression model

Description

Usage

Value

Arguments

Examples