How to Parallelize Your Own Language Using OpenCilk Components

PACT 2021 Tutorial

Tao B. Schardl, MIT
I-Ting Angelina Lee, WUSTL

Please note:
- Times are Eastern Daylight Time (EDT)
- To participate in the hands-on exercises, you will need to use docker.
- Docker image for hands-on sections (800MB).
- Docker script for launching and running the docker image..
- Docker clues.
- Slack channel for questions.
- Slides.
- Video.

3:00 PM - Introduction

Hands-on: download docker image

3:15 PM - What is OpenCilk?

Basics of recursive fork-join parallel programming

Cilk keywords: cilk_spawn, cilk_sync, cilk_for

The serial-projection property

Cilk scheduling

Cilk programming hands-on exercise
Debugging race conditions

Determinacy races

Finding races using Cilksan

What is parallelism?

Work, span, and parallelism

Measuring parallel scalability using Cilkscale

Hands-on exercise using OpenCilk

4:15 PM - Break

4:30 PM - OpenCilk Runtime and Compiler Components

Cheetah runtime system

Work stealing and the work-first principle

Organization of the runtime

Cheetah Hands-On Exercise

OpenCilk compiler middle-end

Tapir representation of recursive fork-join parallelism

Compiler pipeline with Tapir

Optimizations on Tapir

Middle-end Hands-On Exercise

6:10 PM - Break

6:25 PM - Tools

Productivity tools: Cilksan and Cilkscale

Compiler instrumentation

Runtime components

Productivity Tools: Hands-On Exercise

7:00 PM - The End
PREREQUISITE KNOWLEDGE
Familiarity with LLVM compiler fundamentals; interest in parallel programming