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Intermediate Topic 31 of 51 Concurrency & Parallelism

Task Parallelism

Running different tasks at the same time.

How it works

Task parallelism runs different tasks, possibly with different code, concurrently, such as separate stages of a pipeline, independent function calls or a graph of tasks with dependencies. A scheduler assigns tasks to workers, and frameworks provide task graphs, futures, work-stealing schedulers and dependency tracking, as in Intel TBB, Cilk, Java's ForkJoin and .NET's Task Parallel Library. It suits irregular and heterogeneous workloads.

Where it is used

Compilers running independent passes, game engines running animation, physics and AI systems in parallel, build systems executing independent targets and workflow engines use task parallelism.

Common pitfall

Dependencies between tasks limit parallelism, and tasks that are too fine-grained add scheduling overhead while coarse ones cause imbalance. Shared resources create contention. Deadlocks arise from circular waiting. Work-stealing helps balance load but loses locality. Express dependencies explicitly, tune task granularity and profile to find the critical path.

Where it fits in the course

Task Parallelism is topic 31 of 51 in Concurrency & Parallelism, rated Intermediate. It follows Data Parallelism. The next topic is Fork-Join Model.

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 Task Parallelism?
Running different tasks at the same time. It belongs to Concurrency & Parallelism and is an intermediate-level topic.
Where do people use Task Parallelism?
Compilers running independent passes, game engines running animation, physics and AI systems in parallel, build systems executing independent targets and workflow engines use task parallelism.
What is the most common mistake with Task Parallelism?
Dependencies between tasks limit parallelism, and tasks that are too fine-grained add scheduling overhead while coarse ones cause imbalance.
What should I learn before this topic?
Start with Data Parallelism, 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 Task Parallelism hard to learn?
It is an Intermediate topic. Be comfortable with the Beginner topics in this area first, then read the common pitfall carefully, since it is where most mistakes happen.
How long does it take to learn Task Parallelism?
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 Task Parallelism?
Data Parallelism, Fork-Join Model, Software Transactional Memory are closely connected. The full list is in the related topics section of this page.
What should I study after Task Parallelism?
Continue with Fork-Join Model, the next topic in Concurrency & Parallelism.

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