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Is parallel I/O suitable for mission-critical applications?

Parallel computing technology has not seen widespread use in the business world, but could that change? Jon Toigo discusses parallel I/O for applications and where it might fit in.

One common question asked in virtually any discussion of parallel computing or parallel I/O is whether deployed...

mission-critical applications can take advantage of the technology. From the standpoint of business applications, the answer is clearly "no." Most applications deployed today rely on sequential processing -- instruction after instruction, processed in series.

But there are parallel computing-ready applications. Parallel databases, and to a certain extent, parallel file systems, have been used within the rarified world of high-performance computing for quite some time. However, these applications tend to be found within the narrow domains of government research labs and computer science departments of technical colleges and universities.

Signs that parallel techs are gaining interest

There are prospects that parallel technologies may find more widespread application in the business world, especially with the increased interest in big data analytics. For now, the use of parallel applications is just not that widespread.

There are prospects that parallel technologies may find more widespread application in the business world, especially with the increased interest in big data analytics.

Moreover, the holy grail of parallel computing -- a simple and automatic way to convert programs designed for sequential execution so they can use parallel computing architecture instead -- has yet to appear. Most applications, including the most demanding hypervisor-computing workloads, are simply sequentially architected wares that issue instructions as a series of requests on a shared resource, called a logical core, that at best simulate concurrent or parallel execution.

Those facts should not be viewed as limitations of parallel I/O to business computing. In fact, the application targeted by parallel I/O is not specifically the acceleration of business applications, operating systems or virtual machines. Rather, the application that is the focus of parallel I/O is the handling of I/O requests in a concurrent manner from multiple, hosted application software processes.

From multiprocessor to multicore

With the multiprocessor environments of the 1980s and 1990s, each processor handled an application. In some designs, a processor or group of processors was dedicated to doing nothing but processing, in parallel, all the I/O generated by the discrete application-processing CPUs. Lately, that design has been transferred to multicore processors.

In a multicore processor, there are two or more actual processing units called cores. Each core functions as a separate CPU to read and execute program instructions, usually with its own caches that can read instructions separately from the other physical cores on a chip. In addition to the physical multicore architecture, there is typically a set of processes -- software abstractions -- running in a contemporary chip, aka hyper-threading in Intel chips, that creates logical cores. Logical cores are also processing units that are capable of executing their own threads in parallel with other logical cores.

Next Steps

Parallel computing design can unlock the power of multicore processors

Parallel computing architecture not suited for every task

Storage leaders in the dark about I/O's impact on core applications

This was last published in November 2015

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Which parallel I/O-ready applications have you worked with?
Parallel processing has its place.  The problem is you need an o/s that can handle the requirements well.  That probably meens a *Nix environment.

Outside of a few analytics platforms, there aren't many parallel applications intended or suitable to commercial use.

But data and database parallelization is a technology that, with proper training and IT architecture planning, can be implemented and maintained by commercial enterprise IT. This has proven to be an excellent method to avoid problems often associated with large, distributed databases. This architecture is often used to provide wide area data availability and to mitigate issues such as slow inquiry response, long lag times and WAN latency issues.