IBM Systems Magazine, Power Systems - September 2016 - 22

"You'll see an increasing focus from IBM on optimization of Spark on POWER as well as different tooling becoming available from IBM and its partners." -Steve Roberts, big data offering manager, Power Systems clusters with a preloaded Hadoop and Spark software stack. The addition of Linux* OScentric Power Systems servers with the S822L and S812L offerings in 2014 continued the big data revolution. These scaleup servers are especially costeffective for running big data workloads, Roberts says. Realizing that clients also needed a storage-dense model to run Hadoop and Spark, IBM delivered the LC line in 2015. The S812LC has all of the processor advantages of POWER8 servers in terms of memory, threads and cache as well as the capability to hold 14 large form factor hard disk drives or SSDs. As Spark grows in popularity, IBM is focusing on building more optimized solutions that include larger memory configurations and higher speed disk access through SSD flash storage to support Spark's intensive in-memory applications, Roberts says. The POWER Advantage Many big data systems run on clusters, requiring efficient networking and disk I/O subsystems. The combination of compute processing, network and I/O capabilities allows Power Systems servers to run Hadoop and Spark workloads more efficiently than x86, Krishnamurthy says. Higher main memory bandwidth and larger caches on POWER servers means workloads are processed faster. "With 4x more cache, Power Systems can yield higher performance than x86," Krishnamurthy says. Further, Java* Development Kits (JDKs), including IBM JDK and OpenJDK, are optimized for POWER technology, allowing Hadoop and Spark to operate faster. Running Spark on POWER processors can achieve an average of 70 percent higher performance than a similar x86 system for a range of Spark workloads, Krishnamurthy says. That means 50 percent higher performance per dollar across that same range of Spark workloads than x86. According to IBM 22 // SEPTEMBER 2016 ibmsystemsmag.com internal testing (ibm.co/1Y2PbZl), for some machine-learning workloads-such as logistic regression-POWER servers can actually achieve 2x higher performance per dollar over x86 systems. For some SQL workloads, Power Systems achieve 1.7x higher performance per dollar over x86 systems, he says. Demand for systems that can handle petabytes of data have grown more common, putting emphasis on storage systems. A classic Hadoop architecture requires triple copies of data, which means adding nodes in x86, Roberts says. Power Systems clients no longer need to add nodes to get storage. For example, because IBM offers a converged storage solution, a large Middle East telecommunications company deployed on one- http://ibm.co/1Y2PbZl http://ibm.co/1Y2PbZl http://www.ibmsystemsmag.com

Table of Contents for the Digital Edition of IBM Systems Magazine, Power Systems - September 2016

Table of Contents
Editor's Desk: Volume, variety, velocity
IBM Perspective: Spark on Power: winning the race to faster insight
Techbits: Watson hits the road
Partner PoV: Five ways to protect your organization from disaster
R&D: Collaborative computing leads to a better understanding of the earth's interior
Case Study: Hooked on Data: SilverHook Powerboats pioneers the use of data from the Internet of Things
Cover Story: Unlocking Business Value: Why Hadoop and Spark big data workloads perform better on Power
Feature: Spark Ignites Big Data Processing: IBM researchers examine how to get the most out of Spark
Tech Showcase: Recent trends in high availability show enterprises expect at least 99.9 percent uptime
Trends: DevOps unites developers with operations staff to support the dynamic needs of web applications
Solutions: API Integration Platform 3.0; Field Encryption for IBM i, Navigator Family, Implementer 12.0
Snapshot: Liam Allan
Reference Point - Global Events, Education, Resources for Power Systems
2016 Power Systems Solution Edition Product Index
IBM Systems Magazine, Power Systems - September 2016 - Intro
IBM Systems Magazine, Power Systems - September 2016 - Cover1
IBM Systems Magazine, Power Systems - September 2016 - Cover2
IBM Systems Magazine, Power Systems - September 2016 - 1
IBM Systems Magazine, Power Systems - September 2016 - Table of Contents
IBM Systems Magazine, Power Systems - September 2016 - 3
IBM Systems Magazine, Power Systems - September 2016 - 4
IBM Systems Magazine, Power Systems - September 2016 - 5
IBM Systems Magazine, Power Systems - September 2016 - Editor's Desk: Volume, variety, velocity
IBM Systems Magazine, Power Systems - September 2016 - 7
IBM Systems Magazine, Power Systems - September 2016 - IBM Perspective: Spark on Power: winning the race to faster insight
IBM Systems Magazine, Power Systems - September 2016 - Techbits: Watson hits the road
IBM Systems Magazine, Power Systems - September 2016 - Partner PoV: Five ways to protect your organization from disaster
IBM Systems Magazine, Power Systems - September 2016 - 11
IBM Systems Magazine, Power Systems - September 2016 - R&D: Collaborative computing leads to a better understanding of the earth's interior
IBM Systems Magazine, Power Systems - September 2016 - 13
IBM Systems Magazine, Power Systems - September 2016 - 14
IBM Systems Magazine, Power Systems - September 2016 - 15
IBM Systems Magazine, Power Systems - September 2016 - Case Study: Hooked on Data: SilverHook Powerboats pioneers the use of data from the Internet of Things
IBM Systems Magazine, Power Systems - September 2016 - 17
IBM Systems Magazine, Power Systems - September 2016 - 18
IBM Systems Magazine, Power Systems - September 2016 - 19
IBM Systems Magazine, Power Systems - September 2016 - Cover Story: Unlocking Business Value: Why Hadoop and Spark big data workloads perform better on Power
IBM Systems Magazine, Power Systems - September 2016 - 21
IBM Systems Magazine, Power Systems - September 2016 - 22
IBM Systems Magazine, Power Systems - September 2016 - 23
IBM Systems Magazine, Power Systems - September 2016 - 24
IBM Systems Magazine, Power Systems - September 2016 - 25
IBM Systems Magazine, Power Systems - September 2016 - Feature: Spark Ignites Big Data Processing: IBM researchers examine how to get the most out of Spark
IBM Systems Magazine, Power Systems - September 2016 - 27
IBM Systems Magazine, Power Systems - September 2016 - 28
IBM Systems Magazine, Power Systems - September 2016 - 29
IBM Systems Magazine, Power Systems - September 2016 - 30
IBM Systems Magazine, Power Systems - September 2016 - Tech Showcase: Recent trends in high availability show enterprises expect at least 99.9 percent uptime
IBM Systems Magazine, Power Systems - September 2016 - 32
IBM Systems Magazine, Power Systems - September 2016 - 33
IBM Systems Magazine, Power Systems - September 2016 - 34
IBM Systems Magazine, Power Systems - September 2016 - 35
IBM Systems Magazine, Power Systems - September 2016 - 36
IBM Systems Magazine, Power Systems - September 2016 - 37
IBM Systems Magazine, Power Systems - September 2016 - 38
IBM Systems Magazine, Power Systems - September 2016 - 39
IBM Systems Magazine, Power Systems - September 2016 - 40
IBM Systems Magazine, Power Systems - September 2016 - 41
IBM Systems Magazine, Power Systems - September 2016 - Trends: DevOps unites developers with operations staff to support the dynamic needs of web applications
IBM Systems Magazine, Power Systems - September 2016 - 43
IBM Systems Magazine, Power Systems - September 2016 - 44
IBM Systems Magazine, Power Systems - September 2016 - 45
IBM Systems Magazine, Power Systems - September 2016 - Solutions: API Integration Platform 3.0; Field Encryption for IBM i, Navigator Family, Implementer 12.0
IBM Systems Magazine, Power Systems - September 2016 - 47
IBM Systems Magazine, Power Systems - September 2016 - Snapshot: Liam Allan
IBM Systems Magazine, Power Systems - September 2016 - Cover3
IBM Systems Magazine, Power Systems - September 2016 - Cover4
IBM Systems Magazine, Power Systems - September 2016 - Reference Point - Global Events, Education, Resources for Power Systems
IBM Systems Magazine, Power Systems - September 2016 - 2016 Power Systems Solution Edition Product Index
IBM Systems Magazine, Power Systems - September 2016 - SE2
IBM Systems Magazine, Power Systems - September 2016 - SE3
IBM Systems Magazine, Power Systems - September 2016 - SE4
IBM Systems Magazine, Power Systems - September 2016 - SE5
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