What is the difference between Concurrent Transmission/Processing vs Parallel Transmission/Processing ?
Concurrency is when two tasks can start, run, and complete in overlapping time periods. It doesn't necessarily mean they'll ever both be running at the same instant. Eg. multitasking on a single-core machine.
Parallelism is when tasks literally run at the same time, eg. on a multicore processor.
The term Parallelism refers to techniques to make programs faster by performing several computations in parallel. This requires hardware with multiple processing units. In many cases the sub-computations are of the same structure, but this is not necessary. Graphic computations on a GPU are parallelism.
The term Concurrency refers to techniques that make program more usable. Concurrency can be implemented and is used a lot on single processing units, nonetheless it may benefit from multiple processing units with respect to speed. If an operating system is called a multi-tasking operating system, this is a synonym for supporting concurrency. If you can load multiple documents simultaneously in the tabs of your browser and you can still open menus and perform more actions, this is concurrency. If you run distributed-net computations in the background, that is concurrency.
Concurrency and parallelism are NOT the same thing. Two tasks T1 and T2 are concurrent if the order in which the two tasks are executed in time is not predetermined,
T1 may be executed and finished before T2,
T2 may be executed and finished before T1,
T1 and T2 may be executed simultaneously at the same instance of time (parallelism),
T1 and T2 may be executed alternatively,
If two concurrent threads are scheduled by the OS to run on one single-core non-SMT non-CMP processor, you may get concurrency but not parallelism. Parallelism is possible on multi-core, multi-processor or distributed systems.
Concurrency is often referred to as a property of a program, and is a concept more general than parallelism.
Interestingly, we cannot say the same thing for concurrent programming and parallel programming. They are overlapped, but neither is the superset of the other. The difference comes from the sets of topics the two areas cover. For example, concurrent programming includes topic like signal handling, while parallel programming includes topic like memory consistency model. The difference reflects the different orignal hardware and software background of the two programming practices.
Concurrency is when two tasks can start, run, and complete in overlapping time periods. It doesn't necessarily mean they'll ever both be running at the same instant. Eg. multitasking on a single-core machine.
Parallelism is when tasks literally run at the same time, eg. on a multicore processor.
The term Parallelism refers to techniques to make programs faster by performing several computations in parallel. This requires hardware with multiple processing units. In many cases the sub-computations are of the same structure, but this is not necessary. Graphic computations on a GPU are parallelism.
The term Concurrency refers to techniques that make program more usable. Concurrency can be implemented and is used a lot on single processing units, nonetheless it may benefit from multiple processing units with respect to speed. If an operating system is called a multi-tasking operating system, this is a synonym for supporting concurrency. If you can load multiple documents simultaneously in the tabs of your browser and you can still open menus and perform more actions, this is concurrency. If you run distributed-net computations in the background, that is concurrency.
Concurrency and parallelism are NOT the same thing. Two tasks T1 and T2 are concurrent if the order in which the two tasks are executed in time is not predetermined,
T1 may be executed and finished before T2,
T2 may be executed and finished before T1,
T1 and T2 may be executed simultaneously at the same instance of time (parallelism),
T1 and T2 may be executed alternatively,
If two concurrent threads are scheduled by the OS to run on one single-core non-SMT non-CMP processor, you may get concurrency but not parallelism. Parallelism is possible on multi-core, multi-processor or distributed systems.
Concurrency is often referred to as a property of a program, and is a concept more general than parallelism.
Interestingly, we cannot say the same thing for concurrent programming and parallel programming. They are overlapped, but neither is the superset of the other. The difference comes from the sets of topics the two areas cover. For example, concurrent programming includes topic like signal handling, while parallel programming includes topic like memory consistency model. The difference reflects the different orignal hardware and software background of the two programming practices.
Concurrent processing is word related to serial programming. trying to do task in parallel. so called Concurrent processing.
parallel processing is term useful on both single processor and multiprocessor system and working on it.
In fact, parallel processing is possible on multiprocessor/multicore.
Concurrency means run multiple processes on a single processor simultaneously , while Parallelism means run multiple processes on multiple processors simultaneously. Hope that helps
Concurrency and parallelism are two terminologies that in not accurate to use VS. between them , basically because one is used in transaction of Database systems and the other is used for processing methods.
well concurrency means all related transactions must be committed simultaneously, parallel processing could be one of the solutions to ensure concurrency to keep our distributed data base integrated and consistent
Concurrency means that two or more processes fight for the same resource. E.g. two transmitters fight for channel access in random access scheme or two tasks fight for processor in single processor system.
Parallelism means that two or more processes execute simultaneously. E.g. two transmitters transmit simultaneously over two different channels or two tasks execute simultaneously on two different processors.
Moreover, some use term parallel processing for two or more active processes sharing the same processor concurrently. Note that, in this case, only one process can be in running state. All the other processes are in ready or sleep states waiting to be scheduled for execution. Since, processes are active simultaneously; one can say they are active in parallel, but they access processor concurrently.
Concurrency, means that you have concurrent accesses to one or more shared resources in a system (operating system, database system, etc...). Concretely, two or more threads (or processes) make accesses to a given resources or set of resources. You can perfectly gave concurrency without parallelism. If two or more threads that are running on a single-core CPU, or on the same core in a multi-cores CPU, they can concurrently access to the same resources even if their execution is in pseudo-parallelism. This usually means that you have to deal with mutual exclusion if you want to avoid data incoherency problems, in the case of write (modification) accesses.
Parallelism means that two or more processes (or threads) are running in parallel (I mean here not in pseudo-parallelism like in single-core processors, but in real parallelism like in multi--cores). Parallelism may involve concurrency of the threads or processes sharing one or more resources and making write operations (modifications) on these resources. Concurrency for read operations exists but is not a major concern as it does not generate coherency problems. Now, we can perfectly have parallelism without concurrency, if no resource is shared.
In operating systems, we can also say that several processes or threads running on the same core are making a concurrent use of the processor (core). They are all in competition to obtain the processor.
There is effectively no difference between pseudo-parallelism and real parallelism from the possible concurrent accesses point of view. The only difference is that things will go faster with real parallelism.
Anyway, in some rare cases with pseudo parallelism, we can have potential concurrent accesses (write accesses for example) to a given resource from several threads, but this will luckily work! This is because in pseudo-parallelism (on a single CPU), even if we have concurrent accesses, they are sequential. The problem is when a task or thread commutation occurs when a thread did not achieve to terminate its write access before its execution quantum ends. So if you are lucky, a parallel program could work without generating coherency problems. But this is pure luck!
When things really work in parallel (real parallelism on multiple CPUs or on a multi-core CPU), you have to be very very lucky for your program to work correctly without any synchronization techniques. This is because without synchronization, there is not any kind of sequential execution among threads. To be honest, in every case, you need to use synchronization techniques like mutual exclusion to ensure that you program will correctly work. Being lucky, is never a good choice for parallel programming :-)
To my understanding, concurrency denotes asynchronous execution. That means that two computational processes execution can overlap at some point in time. A parallel execution means that two computational processes are run in parallel both starting at the same point in time.
the danger is always that words mean only what you want them to mean. in this case, these words are problematic because they do not have a clear distinction in English, and, as some messages here demonstrate, even in very narrow fields, their meanings are subtle.
for "concurrent" to have any meaning, it must refer to two or more things actually happening at once - con+current. the same is certainly true of parallelism, though there is a somewhat visual/geometric reference here: parallel weakly implies that the same things are happening concurrently, like SIMD.
my first point is simply that this distinction is subtle enough that we shouldn't rely on the two words to distinguish cases in discussion.
In terms of processing, i cite this definition that appears on "A Survey on Parallel Computing and its Applications in Data-Parallel Problems Using GPU Architectures",
Commun. Comput. Phys, September 2013.
"Definition 2.1. Concurrency
is a property of a program (at design level) where two or more tasks can be in progress simultaneously.
Definition 2.2. Parallelism is a run-time property where two or more tasks are being executed simultaneously.
There is a difference between being in progress and being executed
since the first one does not necessarily involve being in execution. Let
C and P be concurrency and parallelism, respectively, then P⊂C. In other words, parallelism requires concurrency, but concurrency does not require parallelism. A nice example where both concepts come into play is the operating system (OS); it is concurrent by design (performs multi-tasking so that many tasks are in progress at a given time) and depending on the number of physical processing units, these tasks can run parallel or not."
An analogy at its most basic:
I am ironing clothes whilst the washing machine is on.
I am processing the items of clothing in turn, i.e. I can't iron a shirt and a towel at the same time. One comes after the other.
The washing machine is running in parallel to my ironing. Nothing I do about the ironing, faster or slower, more of it, less of it, more people, less people working on the ironing, or whatever, makes the washing machine cycle go faster or slower. The two processes are running in parallel.
While I routinely watch TV, a small amount of the resource I am using is concentrating on the TV and a small amount of concentration is going into the ironing. Suddenly something comes on TV which is really, really interesting or important. My concentrating on the TV increases markedly and I may even stop ironing to give it my full attention. This is concurrency. The TV and the ironing are going on at the same time but they are calling on the same resource.
Turn the radio on at the same time as the TV and the resource for concurrent processing is overwhelmed. We might need to concentrate on the radio then switch our attention back to the TV - certainly we are not going to be continuing with the ironing (unless especially deft).
Breaking the management of these tasks up is the same sort of thing that we see when we start talking about pre-emptive and co-operative multitasking, but there are other ways to do the best of what we can when we are sharing a finite resource amongst tasks.
Meantime the whole process of ironing, looked up as itself is either coming along more or less slowly dependent on the resource priority we attach to it. And the washing machine is happily doing its thing, not affected at all. It is effectively running on its own processor.
Have a look please
http://joearms.github.io/2013/04/05/concurrent-and-parallel-programming.html
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