EP>(Вообще говоря и параллельное и конкурентное программирование охватывают бОльшие области чем я описал, но для первого приближения такого описания достаточно)

https://en.wikipedia.org/wiki/Concurrent_computing
Concurrent computing is related to but distinct from parallel computing, though these concepts are frequently confused,[2][3] and both can be described as "multiple processes executing during the same period of time". In parallel computing, execution literally occurs at the same instant, for example on separate processors of a multi-processor machine, with the goal of speeding up computations – parallel computing is impossible on a (single-core) single processor, as only one computation can occur at any instant (during any single clock cycle).[a] By contrast, concurrent computing consists of process lifetimes overlapping, but execution need not happen at the same instant. The goal here is to model processes in the outside world that happen concurrently, such as multiple clients accessing a server at the same time. Structuring software systems as composed of multiple concurrent, communicating parts can be useful for tackling complexity, regardless of whether the parts can be executed in parallel.[4]:1

For example, concurrent processes can be executed on a single core by interleaving the execution steps of each process via time slices: only one process runs at a time, and if it does not complete during its time slice, it is paused, another process begins or resumes, and then later the original process is resumed. In this way multiple processes are part-way through execution at a single instant, but only one process is being executed at that instant.

Concurrent computations may be executed in parallel,[2][5] for example by assigning each process to a separate processor or processor core, or distributing a computation across a network, but in general, the languages, tools and techniques for parallel programming may not be suitable for concurrent programming, and vice versa.

https://en.wikipedia.org/wiki/Parallel_computing
Parallel computing is closely related to concurrent computing – they are frequently used together, and often conflated, though the two are distinct: it is possible to have parallelism without concurrency (such as bit-level parallelism), and concurrency without parallelism (such as multitasking by time-sharing on a single-core CPU).[5][6] In parallel computing, a computational task is typically broken down in several, often many, very similar subtasks that can be processed independently and whose results are combined afterwards, upon completion. In contrast, in concurrent computing, the various processes often do not address related tasks; when they do, as is typical in distributed computing, the separate tasks may have a varied nature and often require some inter-process communication during execution.

http://talks.golang.org/2012/waza.slide#1
Concurrency is not Parallelism

M>Ну то есть все остальное приходится закатывать вручную — изоляцию потоков, разделение данных, управление потоками и т.п. Ты смотри. Как раз то, о чем я говорил в изначальном сообщении

int F(int){...}
int main()
{
    auto d=LoadData();
    #pragma omp parallel for
    for(int i=0; i<d.size(); i++) d[i]=F(d[i]);
    SaveData(d);
}

_>int F(int){...}
_>int main()
_>{
_>    auto d=LoadData();
_>    #pragma omp parallel for
_>    for(int i=0; i<d.size(); i++) d[i]=F(d[i]);
_>    SaveData(d);
_>}
_>

int F(int){...}
int main()
{
    auto d=LoadData();
    parallel_transform(begin(d), end(d), begin(d), F);
    SaveData(d);
}