Why Performance is Critical to your Digital Transformation Strategy and How Parallel Computing Helps

Need For Speed
April 16, 2018
Webinar Q&A: z/OS Mainframe SIEM Data Overload! How to Cut Through The Noise! Sponsored by Software Diversified Services
May 11, 2018
Need For Speed
April 16, 2018
Webinar Q&A: z/OS Mainframe SIEM Data Overload! How to Cut Through The Noise! Sponsored by Software Diversified Services
May 11, 2018

Why Performance is Critical to your Digital Transformation Strategy and How Parallel Computing Helps

By Haluk Ulubay, Senior Director of Marketing, DataCore Software

Businesses today are overwhelmingly embracing digital transformation as a key strategic priority. However, to be successful in achieving this transformation, real-time data is critical. This is because in today’s 24×7 business environment, an organization’s ability to remain competitive lies in its ability to quickly react and align with customer expectations.

However, real-time data often proves challenging for today’s enterprises. During peak periods when many users or tasks compete for data access, systems are often bogged down as simultaneous requests are serialized, waiting on previous requests to complete. For example, imagine that you’re trying to buy something online but when you go to complete the order, the item is shown as out of stock, simply because the underlying inventory control process takes too long to provide current data. This inability to quickly respond is how poor customer experiences are created—ultimately hurting business.

What is the root cause of these performance bottlenecks? One important, but relatively hidden, performance bottleneck exists in the OS as it passes I/O between the CPU and storage in a single threaded, interrupt-based manner. This is what slows things down.

IT departments have tried to fix this in a number of ways; for example, by installing costly all-flash storage either in the systems themselves or by using an all-flash array, but that still won’t remove the bottleneck in the OS. It’s true that the I/O that’s in flight to or from storage might arrive at its destination faster, but the application will be bottlenecked by single threaded I/O.

A type of parallel computing may be the key to gaining more speed. An example of this is Parallel I/O technology which leverages the power of multicore servers to overcome the I/O bottleneck by enabling multiple input/output operations simultaneously. This, in turn, helps eliminate the I/O bottlenecks that can stop or impair the flow of data.

Rather than process I/O requests serially, one at a time, Parallel I/O technology accesses data from storage simultaneously across multiple threads. This allows a system to achieve higher data read/write speeds and maximizes bandwidth. With Parallel I/O, a portion of the logical cores on the multicore chip are used as needed to process I/O from any applications running on the system. This allows the processor to not switch context, allowing applications to run concurrently.

DataCore MaxParallel™

DataCore MaxParallel™ applies Parallel I/O to solve application-specific problems. MaxParallel makes workloads more responsive and productive by removing a number of chokepoints in the operating system responsible for sluggish behavior and under-utilized hardware resources. This plug-and-play software requires no changes to data, applications or hardware, and schedules independent access to data in parallel, eliminating much of the queueing delays at the root of the problem. The process puts idle cores to work on these high-priority I/O-intensive demands to take full advantage of available resources.

Microsoft Exchange Server, Oracle databases, MySQL databases, and other similar high-throughput workloads benefit from a much-needed I/O performance boost, allowing more work to be completed with fewer resources while reducing infrastructure costs through more productive use of server cores and memory. This also adds the potential to save on licensing costs.

Furthermore, MaxParallel is easy to install and enables the user to experience higher productivity in minutes. It installs into the Windows Operating System, and runs as a service. Once installed, it works by using idle cores to push more work through to storage. There is no modification required to the workload application (database, etc.) or additional hardware required. With a single reboot during your existing maintenance window, it’s ready to go.

“What is the end result,” you ask? MaxParallel users have reported 20 to 50% higher productivity from Windows Server. Try MaxParallel now to set your organization on the right path to achieving its digital transformation goals.