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## Definition

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```{image} ./../_static/concurrency.png
:alt: Concurrency
:width: 100%
```

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### Concurrency
The ability of a system to progress in multiple tasks through  

- **simultaneous execution**
- **context switching**
- **coordination**
- **process control**
- **managing interactions**
- **managing resources**

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:::{figure} ./../_static/concurrency.png
:figclass: margin
:alt: Concurrency
:width: 100%
:::

```{epigraph}
The ability of a system to progress in multiple tasks through simultaneous execution, context switching, coordination, process control, managing interactions and resources.
```

In other words, concurrency is the ability of a computer system to handle multiple tasks with overlapping lifetimes, rather than running them strictly one after another.
It allows a program to be decomposed into independent segments that can run in parallel, be paused, or be resumed without altering the final outcome.

A concurrent system efficiently utilizes its computational capacity by avoiding idle time (e.g., switching to another task while waiting for data from RAM).

### Example: Data Processing Pipeline

Consider a program that needs to download and process multiple large datasets:
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:::::{grid-item-card} Sequential Approach
::::{grid} 1 1 1 2
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:::{grid-item-card} Process 1:
- Fetch dataset 1 (30 sec)
- Process (60 sec)
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:::{grid-item-card} Process 2:

- **Fetch dataset 2 (30 sec)**
- Process (60 sec)
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**Total: 180 seconds**
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:::::{grid-item-card} Concurrent Approach
::::{grid} 1 1 1 2
:gutter: 2

:::{grid-item-card} Process 1:
- Fetch dataset (30 sec)
- Process (60 sec)
:::
:::{grid-item-card} Process 2:
- **Fetch dataset 2 during Process 1**
- Process (60 sec)
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**Total: 150 seconds** (17% faster)
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This illustrates how concurrency exploits natural waiting periods.
While the CPU processes one dataset, the network interface downloads another, keeping both resources actively utilized rather than leaving one idle.

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