Difference Between Concurrency And Parallelism

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What is Concurrency?

Concurrency refers to the execution of multiple instruction sequences at the same time. It occurs in an operating system when multiple process threads are executing concurrently. These threads can interact with one another via shared memory or message passing. Concurrency results in resource sharing, which causes issues like deadlocks and resource scarcity. It aids with techniques such as process coordination, memory allocation, and execution schedule to maximize throughput.

What is Parallelism?

Parallellism refers to the process of executing several processors an application or computation simultaneously. Generally, it is a kind of computing architecture where the large problems break into independent, smaller, usually similar parts that can be processed in one go. It is done by multiple CPUs communicating via shared memory, which combines results upon completion. It helps in performing large computations as it divides the large problem between more than one processor.

Parallellism also helps in faster application processing and task resolution by increasing the available computation power of systems. The principle of parallelism (parallel computing) is used by most supercomputers in their operation. The operational scenarios that need massive processing power or computation, generally, parallel processing is commonly used there.

Also Read: Difference Between Duo Core And Core 2 Duo

Concurrency vs Parallelism

CONCURRENCY PARALLELISM
Concurrency refers to the execution of multiple instruction sequences at the same time. Parallelism is when tasks literally run at the same time e.g on a multi-core processor.
Concurrency is about dealing with lots of things at once. Parallelism is about doing lots of things at once.
Concurrency is slower than parallelism. Parallelism is faster than concurrency.
Concurrency is achieved through the interleaving operation of processes on the central processing unit (CPU) or in other words by the context switching. Parallelism is achieved through multiple central processing units (CPUs).
In concurrency, debugging is very hard.   In parallelism, debugging is also hard but simple than concurrency.
Concurrency can be done by using a single processing unit. Parallelism requires hardware with multiple processing units.
Concurrency increases the amount of work finished at a time. It improves the throughput and computational speed of the system.
Concurrency is the non-deterministic control flow approach. Parallelism is a deterministic control flow approach.
Concurrency is essentially applicable when we talk about minimum two tasks or more. Parallelism does not require two tasks to exist.  

What you need to know about Concurrency

  • Concurrency means multiple tasks which start, run, and complete in overlapping time periods, in no specific order.
  • Concurrency is essentially applicable when we talk about minimum two tasks or more. 
  • Concurrency is about dealing with lots of things at once.
  • An application can be concurrent – but not parallel, which means that it processes more than one task at the same time, but no two tasks are executing at same time instant.
  • Concurrency is achieved through the interleaving operation of processes on the central processing unit(CPU) or in other words by the context switching.
  • In concurrency debugging is very hard.

What you need to know about parallelism

  • Parallelism is when tasks literally run at the same time, eg. on a multi-core processor.
  • Parallelism requires a multi processing hardware or you may not be able to get parallelism. 
  • Since in parallelism tasks occur simultaneously it’s faster than concurrency.
  • Parallelism does not require two tasks to exist. 
  • Parallelism requires hardware with multiple processing units
  • Parallelism is about doing lots of things at once.
  • An application can be parallel – but not concurrent, which means that it processes multiple sub-tasks of a task in multi-core CPU at same time.
  • Parallelism is achieved through multiple central processing units(CPUs).
  • In Parallelism debugging is also hard but simple than concurrency.