In my previous blog I expressed high expectations for the Big Data-related activities at this year’s Supercomputing. Coming back from the show, I’d say the enthusiasm and knowledge on Big Data within the HPC community truly surprised me. Here are the major highlights from the show:
- Good flow of traffic at the Platform booth for Platform MapReduce. Many visitors stopped by our booth to learn more about Platform MapReduce – a distributed runtime engine for MapReduce applications. I found it easy to talk to the HPC crowd because many folks in this community are already familiar with Platform LSF and Platform Symphony; both are flagship products from Platform that have been deployed and tested in large-scale distributed computing environment for many years. Since Platform MapReduce is built on similar core technology as what’s in those mature products, the HPC community quickly understood the key features and functions it brings to Big Data environments. Even though many users are still at early stage of either developing MapReduce applications or looking into new programming models, they understand that a sophisticated workload scheduling engine and resource management tool will become critically important once they are ready to deploy their applications into production. Many HPC sites were also interested in exploring the potential of leveraging their existing infrastructure for processing data-intensive applications. For instance, questions on how a MPI and MapRedcue jobs can coexist on the same cluster were frequently asked at the show. The good news, Platform MapReduce is the only solution that can provide capability of supporting mixed workloads.
- “Hadoop for Adults” -- This was a quote from one of the attendees after sitting through our breakfast briefing on overcoming MapReduce barriers. We LOVE it! The briefing lured over 130 people and well exceeded our expectations! Our presentation on how to overcome the major challenges in current Hadoop MapReduce implementations drew great interest. “Hadoop for Adults” sums up the distinct benefits Platform MapReduce brings. Platform Computing knows how to manage large-scale distributed computing environments. Bringing that same technology into Big Data environments is a natural extension for us. The reaction at SC’11 for Platform MapReduce was encouraging and a validation on our expertise in scheduling and managing workloads and overall infrastructure in a center.
- Growing momentum on application development. As sophisticated as always, the HPC community is at the forefront of developing applications to solve data-intensive problems across various industries and disciplines: cyber security, bioinformatics, electronic industry and financial services are just a few examples. Many Big Data related projects are being funded at HPC data centers and we are expecting a proliferation of applications coming out of those projects very soon.
The show is officially over but the excitement around Big Data will continue. For me, not only have I gained tremendous insights on the Big Data momentum in HPC, but I’m also pleased to see the overwhelming reaction for Platform MapReduce within the HPC community. Nothing beats pitching the right product to the right audience!