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Turn on your smart phone and it works like charm. But explosive global adoption of smart phones with feature-rich applications is stressing mobile networks like never before. For mobile network providers, the challenge couldn’t be more acute: Find new ways to deliver more mobile bandwidth even as the average revenue per user remains flat.

In this AIS interview, LSI’s Jeff Connell, director of mobile networking product marketing, talks about how network providers are turning to heterogenous networks (HetNets) to reduce the cost of deploying, scaling and managing mobile networks. One way network providers are streamlining deployments is by using equipment built with smart silicon like LSI Axxia. The highly integrated ASIC helps customers cut the cost and power of new network equipment designs.

Reducing network latency
Speed is the currency of smart phone communications. Users want their information without delays. Here, Jon Devlin, director of networking ecosystem at LSI, discusses the importance of reducing network latency for applications including mobile video conferencing and voice over IP.

 

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Pushing your enterprise cluster solution to deliver the highest performance at the lowest cost is key in architecting scale-out datacenters. Administrators must expand their storage to keep pace with their compute power as capacity and processing demands grow.

safijidsjfijdsifjiodsjfiosjdifdsoijfdsoijfsfkdsjifodsjiof dfisojfidosj iojfsdiojofodisjfoisdjfiodsj ofijds fds foids gfd gfd gfd gfd gfd gfd gfd gfd gfd gfdg dfg gfdgfdg fd gfd gdf gfd gdfgdf g gfd gdfg dfgfdg fdgfdgBeyond price and capacity, storage resources must also deliver enough bandwidth to support these growing demands. Without enough I/O bandwidth, connected servers and users can bottleneck, requiring sophisticated storage tuning to maintain reasonable performance. By using direct attached storage (DAS) server architectures, IT administrators can

Diagram of DataBolt technology buffering 6Gb/s SAS media while maintaining a 12Gb/s SAS link.

Beyond price and capacity, storage resources must also deliver enough bandwidth to support these growing demands. Without enough I/O bandwidth, connected servers and users can bottleneck, requiring sophisticated storage tuning to maintain reasonable performance. By using direct attached storage (DAS) server architectures, IT administrators can reduce the complexities and performance latencies associated with storage area networks (SANs). Now, with LSI 12Gb/s SAS or MegaRAID® technology, or both, connected to 12Gb/s SAS expander-based storage enclosures, administrators can leverage the DataBolt™ technology to clear I/O bandwidth bottlenecks. The result: better overall resource utilization, while preserving legacy drive investments. Typically a slower end device would step down the entire 12Gb/s SAS storage subsystem to 6Gb/s SAS speeds. How does Databolt technology overcome this? Well, without diving too deep into the nuts and bolts, intelligence in the expander buffers data and then transfers it out to the drives at 6Gb/s speeds in order to match the bandwidth between faster hosts and slower SAS or SATA devices.

The DataBolt enabled Hadoop server bandwidth is optimized with 12Gb/s SAS.

So for this demonstration at AIS, we are showcasing two Hadoop Distributed File System (HDFS) servers. Each server houses the newly shipping MegaRAID 9361-8i 12Gb/s SAS RAID controller connected to a drive enclosure featuring a 12Gb/s SAS expander and 32 6Gb/s SAS hard drives. One has a DataBolt-enabled configuration, while the other is disabled.

For the benchmarks, we ran DFSIO, which simulates MapReduce workloads and is typically used to detect performance network bottlenecks and tune hardware configurations as well as overall I/O performance.

The primary goal of the DFSIO benchmarks is to saturate storage arrays with random read workloads in order to ensure maximum performance of a cluster configuration. Our tests resulted in MapReduce Jobs completing faster in 12Gb/s mode, and overall throughput increased by 25%.

DataBolt optimization of DFSIO MapReduce tests (MB/s) per cluster slot maps.

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