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Why Adaptive Parallelization Matters

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Why Adaptive Parallelization Matters
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Lately I have found myself engaging in many conversations related to the topic of parallelization and why it matters, particularly to I/O processing. Upon first hearing the phrase ‘Parallel I/O’, people often jump directly to a traditional performance discussion. While there is no doubt application workload performance is improved in a traditional sense (in terms of latency reduction, increase in operations per second, etc.), there is much more to the story, another dimension if you will.

YOU’VE MOST LIKELY BEEN HERE BEFORE

Let’s consider a real-world example we can build on to explain how this works and why it is important. For the sake of simplicity, let’s assume we are standing at a department store checkout area with a single open lane and one cashier. There are 60 customers currently waiting to checkout (or in slightly technical terms, those 60 customers are in queue). Each of the 60 customers is likely to have a varying number of items to checkout, but for the sake of simplicity, let’s assume they are all roughly the same. If it takes the cashier one minute to checkout each customer, the checkout rate is: 1 customer per minute. Pretty simple so far.

Read the entire article here, Why Adaptive Parallelization Matters

via the fine folks at DataCore Software

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DataCore DataCore is the authority on real-time data. The company pioneered software-defined storage and is now bringing its technology to hyperconverged and workload optimization. DataCore empowers IT organizations to achieve always-available, high-performance and highly efficient data. Its patented technology eliminates storage bottlenecks with adaptive parallel I/O optimization, enables zero-downtime synchronous mirroring, and provides a true hardware-agnostic architecture — resulting in flexibility, resource efficiencies, and cost savings. DataCore software is the cornerstone of the next-generation, software-defined data center. DataCore’s value has been proven in more than 10,000 customer deployments across traditional, hyper-converged, cloud, and hybrid environments.

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