Parallel I/O is a subset of parallel computing that performs multiple input/output operations simultaneously. Rather than process I/O requests serially, one at a time, parallel I/O accesses data on disk simultaneously. This allows a system to achieve higher write speeds and maximizes bandwidth.
Parallel computing became popular in the 1970s, based on the principle that larger issues can be divided into multiple, smaller issues that can be solved at the same time. Used most often in high-performance computing, parallelism can help run applications quickly and efficiently.
Multicore chips help give parallel computing its processing power, and make it compatible with most currently deployed servers. In a multicore processor, each physical core enables efficient use of resources by managing multiple requests by one user with Multithreading.
With parallel I/O, a portion of the logical cores on the multicore chip are dedicated to processing I/O from the virtual machines and any applications the remaining cores service. This allows the processor to handle multiple read and write operations concurrently. Parallel I/O helps eliminate I/O bottlenecks, which can stop or impair the flow of data.
Currently, many applications don't utilize parallel I/O, having been designed to use Unicore sequential processing rather than multicore. However, the recent rise in popularity of big data analytics may signal a place for parallel computing in business applications, which face significant I/O performance issues.
Learn more about parallel I/O technology in this introductory video by Isaac Ye from SHARCNET.
AMD and Intel currently offer multicore chips, and DataCore Software recently received notable Storage Performance Council benchmark results for its DataCore Parallel I/O software.