Parallel computing those that use concurrency, 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 are typically some of the greatest obstacles to getting good parallel program performance. A theoretical upper bound on the speed-up of a single program as a result of parallelization is given by Amdahl's law. Traditionally, computer software has been written for serial computation. To solve a problem, an algorithm is constructed and implemented as a serial stream of instructions. These instructions are executed
Embarrassingly parallel are thus well suited to large, Internet-based distributed platforms such as BOINC, and do not suffer from parallel slowdown. The opposite of embarrassingly parallel problems are inherently serial problems, which cannot be parallelized at all. A common example of an embarrassingly parallel problem is 3D video rendering handled by a graphics processing unit, where each frame (forward method) or pixel (ray tracing method) can be handled with no interdependency. Password cracking is another embarrassingly parallel task that is easily distributed on central processing units, CPU cores, or clusters. "Embarrassingly" is used here in the same sense as in the phrase