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Advanced Topic 36 of 51 Concurrency & Parallelism

MPI

Message-passing interface for cluster programming.

How it works

The Message Passing Interface is the standard API for distributed-memory parallel programming, in which processes with separate memory, ranks, communicate by explicit messages. It provides point-to-point operations such as send and receive in blocking and non-blocking forms, collective operations such as broadcast, scatter, gather, reduce and all-reduce, communicators to group processes, derived datatypes and one-sided communication. Implementations such as OpenMPI and MPICH run across clusters with high-speed interconnects.

Where it is used

Supercomputer simulations in weather, physics and chemistry, large-scale linear algebra and distributed training frameworks' communication libraries use MPI.

Common pitfall

Deadlock occurs when sends and receives are mismatched, such as all processes sending first with blocking calls. Communication costs, latency and bandwidth, often dominate, so overlap communication with computation using non-blocking calls. Load imbalance leaves ranks waiting at collectives. Debugging distributed runs is hard. Minimize message counts, use collectives where possible and design data decomposition carefully.

Where it fits in the course

MPI is topic 36 of 51 in Concurrency & Parallelism, rated Advanced. It follows OpenMP. The next topic is CUDA Programming.

Practice and explore

How to study this topic

  1. Read the explanation above and restate the definition in your own words.
  2. Open the interactive lesson and answer its mini quiz.
  3. Read the common pitfall, then write a short example that avoids it.
  4. Check your understanding in the Concurrency & Parallelism quiz, and revisit the topic if you miss a question.

Frequently asked questions

What is MPI?
Message-passing interface for cluster programming. It belongs to Concurrency & Parallelism and is an advanced-level topic.
Where do people use MPI?
Supercomputer simulations in weather, physics and chemistry, large-scale linear algebra and distributed training frameworks' communication libraries use MPI.
What is the most common mistake with MPI?
Deadlock occurs when sends and receives are mismatched, such as all processes sending first with blocking calls.
What should I learn before this topic?
Start with OpenMP, the topic just before it in Concurrency & Parallelism.
How can I practice it?
Answer the mini quiz in the interactive lesson, then take the Concurrency & Parallelism quiz.
Is MPI hard to learn?
It is an Advanced topic. Expect to read the explanation more than once and to connect it with earlier topics. Working through a small example by hand helps most.
How long does it take to learn MPI?
Most learners can read the explanation and finish the interactive lesson in under an hour. Fluency comes from applying the idea, so plan a few short practice sessions with the quiz.
Which topics are related to MPI?
OpenMP, CUDA Programming, Parallel Prefix Sum are closely connected. The full list is in the related topics section of this page.
What should I study after MPI?
Continue with CUDA Programming, the next topic in Concurrency & Parallelism.

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