Parallel computing is a form of computation in which many instructions are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently ("in parallel"). There are several different forms of parallel computing: bit-level parallelism, instruction-level parallelism, data parallelism, and task parallelism. It has been used for many years, mainly in high-performance computing, but interest in it has grown in recent years due to the physical constraints preventing frequency scaling. Parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multicore processors. However, in recent years, power consumption by parallel computers has become a concern. Parallel computers can be roughly classified according to the level at which the hardware supports parallelism—with multi-core and multi-processor computers having multiple processing elements within a single machine, while clusters, MPPs, and grids use multiple computers to work on the same task. Parallel computer programs are more difficult to write than sequential ones, because concurrency introduces several new classes of potential software bugs, of which race conditions are the most common. Communication and synchronization between the different subtasks is typically one of the greatest barriers to getting good parallel program performance. The speed-up of a program as a result of parallelization is given by Amdahl's law.