Haskell provides several mechanisms to support concurrency and parallelism, allowing for efficient and scalable execution of concurrent and parallel computations. Here are the main approaches Haskell offers:

1. Lightweight Concurrency :
   * Haskell offers lightweight threads, also known as "green threads," which are managed within the Haskell runtime system. These threads are lightweight in terms of memory usage and context switching overhead.
   * The `Control.Concurrent` module provides functions for creating and managing lightweight threads in Haskell.
   * Lightweight threads allow you to write concurrent programs that can perform multiple tasks concurrently, making it easier to write highly concurrent applications.

2. Software Transactional Memory (STM) :
   * Haskell provides built-in support for Software Transactional Memory (STM), a concurrency control mechanism that simplifies concurrent programming.
   * STM allows you to define atomic blocks of code that can perform multiple memory operations atomically. This helps avoid common concurrency issues like race conditions and deadlocks.
   * The `Control.Concurrent.STM` module provides functions and types for working with STM in Haskell. 3. Parallelism using `par` and `pseq` :
   * Haskell supports explicit parallelism through the use of the `par` and `pseq` combinators.
   * `par` allows you to express potential parallelism by specifying that a computation can be evaluated in parallel with another computation.
   * `pseq` enforces sequential evaluation, ensuring that one computation is completed before another.
   * These combinators help in expressing fine-grained parallelism and controlling the evaluation order of computations.

4. Parallel Strategies :
   * Haskell provides the `Control.Parallel.Strategies` module, which offers higher-level constructs for expressing parallelism and controlling evaluation strategies.
   * Strategies allow you to define how computations should be evaluated in parallel and provide control over workload distribution and granularity.
   * Strategies can be applied to lists, data structures, and computations to express parallelism more conveniently.

5. Concurrency and Parallelism Libraries :
   - Haskell has a rich ecosystem of libraries for concurrency and parallelism, such as `async`, `conduit`, and `pipes`, which provide additional abstractions and utilities for managing concurrent and parallel computations.