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The cost or complexity of serial algorithms is estimated in terms of the space (memory) and time (processor cycles) that they take. Parallel algorithms need to optimize one more resource, the communication between different processors. There are two ways parallel processors communicate, shared memory or message passing.
Serial memory processing is the act of attending to and processing one item at a time. This is usually contrasted against parallel memory processing, which is the act ...
The HP Nut processor used in many Hewlett-Packard calculators operated bit-serially. [ 2 ] Assuming N is an arbitrary integer number, N serial processors will often take less FPGA area and have a higher total performance than a single N-bit parallel processor.
Parallel versus serial communication In data transmission , parallel communication is a method of conveying multiple binary digits ( bits ) simultaneously using multiple conductors. This contrasts with serial communication , which conveys only a single bit at a time; this distinction is one way of characterizing a communications link .
A massively parallel processor (MPP) is a single computer with many networked processors. MPPs have many of the same characteristics as clusters, but MPPs have specialized interconnect networks (whereas clusters use commodity hardware for networking). MPPs also tend to be larger than clusters, typically having "far more" than 100 processors. [53]
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. [3]
Denote the serial time as and the parallel time as , where + =. Denote the number of processors as N {\displaystyle N} . Hypothetically, when running the program on a serial system (only one processor), the serial part still takes s {\displaystyle s} , while the parallel part now takes N p {\displaystyle Np} .
Serial computers require much less hardware than their bit-parallel counterparts [1] which exploit bit-level parallelism to do more computation per clock cycle. There are modern variants of the serial computer available as a soft microprocessor [ 2 ] which can serve niche purposes where the size of the CPU is the main constraint.