Supermicro® Hadoop Solutions Accelerate Innovation with Launch of EMC® Greenplum® Analytics Workbench at EMC World
1,000 Node High-Performance, Scalable, Compute and Storage Clusters Support Open Test Platform for Apache Hadoop Development Community
San Jose, CA, May 23, 2012 - Super Micro Computer, Inc. (NASDAQ: SMCI), a global leader in high-performance, high-efficiency server technology and green computing, announces its 1,000 node Apache Hadoop cluster is now live with the launch of EMC’s Greenplum Analytics Workbench this week at EMC World in Las Vegas, Nevada. Supermicro joins EMC and their industry leading partners in a collaborative effort to create the world’s largest open lab environment for Apache Hadoop testing and development. This open platform offers Hadoop developers access to a large scale infrastructure for testing, refining and enhancing their Big Data analytics applications.
“Supermicro appreciates the opportunity to collaborate with our technology and solution partners on this landmark Hadoop project,” said Wally Liaw, Vice President Sales, International at Supermicro. “The launch of Greenplum Analytics Workbench is the result of EMC’s creative vision and a tribute to the value of working together to inspire and accelerate innovation in a rapidly developing technology. Supermicro’s contribution supports the Hadoop development community with our most application optimized server and storage solutions for EMC’s Greenplum Analytics Workbench and we look forward to the resulting insights and knowledge sharing so we can further improve our products to deliver the best solutions for this emerging analytics platform.”
Supermicro’s enterprise-class compute and storage systems offer the ideal platform for organizations looking to quickly implement or transition to Hadoop analytics and a flexible, cost-effective path to scalability as business needs evolve. Supermicro offers world-class integration (build & test) and support capabilities. Supermicro’s contribution to the Greenplum Analytics Workbench consists of 1,000 dual-processor nodes with 12,000/24,000 Cores/Threads, 48 Terabytes of memory and 24 Petabytes of storage. System configurations optimized for this installation’s requirements are based on Supermicro 2U SuperServer® Solutions supporting:
- Dual Intel®Xeon® processors
- Up to 192GB RAM with 12 DDR3 RDIMMs
- 5 PCI-E 2.0 expansion slots
- Onboard LSI 2008 6.0Gbps disk controller
- Dual LAN with Intel 82576 Gigabit Ethernet Controller
- Dedicated IPMI remote management port
- 12 hot-swap 3.5” HDDs
- Redundant 500 Watt Platinum Level high-efficiency (94%+) power supplies
"EMC Greenplum is pleased to have Supermicro contributing their systems and integration expertise along with our other technology partners Intel, Mellanox Technologies, Micron, Seagate, Switch and VMware to this development project," said Jim Totte, Director of Business Development at EMC Greenplum. "We worked closely with Supermicro's design teams to fine-tune system specifications for the optimum balance between performance and efficiency during peak power-draw on typical Greenplum Analytics Workbench workloads. We are excited to go live with this test platform to help the global Hadoop developer community and foster innovation in the Big Data analytics field."
For complete information on Supermicro’s high performance, high-efficiency server and storage solutions optimized for Apache Hadoop, visit www.supermicro.com/Hadoop. For more information on Greenplum Analytics Workbench, visit www.greenplum.com/solutions/analytics-workbench.
About Super Micro Computer, Inc. (NASDAQ: SMCI)
Supermicro®(NASDAQ: SMCI), the leading innovator in high-performance, high-efficiency server technology is a premier provider of advanced server Building Block Solutions® for Data Center, Cloud Computing, Enterprise IT, HPC and Embedded Systems worldwide. Supermicro is committed to protecting the environment through its “We Keep IT Green®” initiative and provides customers with the most energy-efficient, environmentally-friendly solutions available on the market.
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