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EMA Impact Brief
DataCore Lowers Server & Storage Costs with Parallel I/O Processing Technology
Date: 03/08/2016 Length: 3 pages Cost: $25.00

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Abstract:
As predicted by Moore's Law, server-processing power has increased by 100% every two years over the last several decades. Until 2007, this improvement was primarily achieved through an increase in the clock rate of the CPU. Around 2007, however, CPU chips reached a critical point. As CPU clock rates increased to achieve faster processing speeds, the power consumption and thermal output of the CPU chips exceeded what was operable within an enclosed server chassis. To address the thermal problem while continuing to increase performance, processor vendors began to deploy multiple cores within the same CPU chip in 2008. This multicore approach elevated processing power without requiring an increase in the clock rate and the associated increase in thermal output. However, as the number of CPU cores has grown from two to four to eight and beyond, a new performance issue has surfaced. The root of the problem is that in virtualized environments only a single CPU core is assigned by the hypervisor to process input/output (I/O) operations.This restriction creates an "I/O gap" between application processing and I/O processing. This situation results in competing  workloads running slower delayed by the serial I/O backlog.

DataCore, a leader in software-defined storage and hyper-converged virtual SAN solutions, has introduced Adaptive Parallel I/O software. The software multiplies the performance of virtualized and hyper-converged systems that operate with multiprocessors. On January 12, 2016, DataCore announced a new world record for price performance ($0.08 / SPC-1 IOPSô) using the industryís highly recognized and peer-reviewed storage benchmark, the SPC-1 benchmark from the Storage Performance Council. This impact brief explores how DataCore's Parallel I/O Processing Technology addresses the I/O backlog of multicore processing, and why alternative approaches fall short in natively addressing the problem.
Author:

Jim Miller, Former EMA Analyst


 




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