01 - Automatic Roofline Modeling (C/C++)

In the advanced tutorials, we take a look on our compiler collection, the Daisytuner Optimizing Compiler Collection (DOCC). The DOCC allows us to analyze the hotspots of the code at compile-time and instrument those parts for run-time. We will demonstrate this on the Roofline model, which is a performance model to estimate the optimization potentials of loops.

Step 1: Compiling with the DOCC

The DOCC is designed as a drop-in replacement for most recent clang and clang++ compilers. To enable the analysis of hotspot regions, add the -mllvm -hotspot and -ldaisy_rtl flags. This will add instrumentation calls to hotspot regions and link the necessary runtime library to collect performance data. The -g flag for debugging information is always encouraged.

on:
  push:
    branches:
      - main
  pull_request:
    types: [opened, reopened, synchronize, ready_for_review]

parameters:
  timeout: 10
  partitions:
    - bellis5

steps:
  build: |
    docc -Xclang -no-opaque-pointers -g -O1 -mllvm -hotspot -o matmul.out matmul.c -ldaisy_rtl

  run:
    matmul:
      command: ./matmul.out

Step 2: Performance Model

We can tell the runners to execute all necessary runs for the Roofline model, by enabling the loops parameter for the benchmarl. Note that the loops flag cannot be used, when the benchmark has not been compiled with DOCC as described aboved.

  run:
    matmul:
      command: ./matmul.out
      measurements: 2
      loops: true

You can find the resulting Roofline model under the Loops Tab in the Daisytuner App.