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This places an upper limit on the length of a parallel data connection that is usually shorter than a serial connection. Complexity: Parallel data links are easily implemented in hardware, making them a logical choice. Creating a parallel port in a computer system is relatively simple, requiring only a latch to copy data onto a data bus.
For consumers, USB and computer networks have replaced the parallel printer port, for connections both to printers and to other devices. Many manufacturers of personal computers and laptops consider parallel to be a legacy port and no longer include the parallel interface. Smaller machines have less room for large parallel port connectors.
Examples of distributed memory (multiple computers) include MPP (massively parallel processors), COW (clusters of workstations) and NUMA (non-uniform memory access). The former is complex and expensive: Many super-computers coupled by broad-band networks. Examples include hypercube and mesh interconnections.
Parallel computer systems have difficulties with caches that may store the same value in more than one location, with the possibility of incorrect program execution. These computers require a cache coherency system, which keeps track of cached values and strategically purges them, thus ensuring correct program execution.
The canonical example of a massively parallel design is the Connection Machine series. Today, such a machine can be built using commodity hardware, an example being the System X. Many commercial systems, like Google, are based on similar designs. Modern GPUs would also be considered massively parallel by the definitions of the 1980s. For all of ...
Parallel SCSI specifications include several synchronous transfer modes for the parallel cable, and an asynchronous mode. The asynchronous mode is a classic request/acknowledge protocol, which allows systems with a slow bus or simple systems to also use SCSI devices. Faster synchronous modes are used more frequently.
An initial version of this model was introduced, under the MapReduce name, in a 2010 paper by Howard Karloff, Siddharth Suri, and Sergei Vassilvitskii. [2] As they and others showed, it is possible to simulate algorithms for other models of parallel computation, including the bulk synchronous parallel model and the parallel RAM, in the massively parallel communication model.
An example of a fine-grained system (from outside the parallel computing domain) is the system of neurons in our brain. [4] Connection Machine (CM-2) and J-Machine are examples of fine-grain parallel computers that have grain size in the range of 4-5 μs. [1]