Applications of IBM Platform Computing solutions for solving graphic analytics and 3D scalable video cloud transcoder problems

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With the rise of big data era, the demand for using high performance computing (HPC) clouds for big data analytics has dramatically increased. IBM Platform Symphony, a new software product by IBM Platform Computing, provides a high performance runtime engine for running distributed applications and big data analytics on a scalable, shared grid. It is designed to maximize the potential of the computing power and the supporting infrastructure to accelerate computationally expensive applications, extract insight from the data, and make better decisions faster. To attract customers in the competitive market for HPC solutions, IBM has expressed a great interest in investigating and demonstrating the applicability of their software in different application domains. We will investigate the applicability and adaptability of IBM Platform Computing solutions (in particular, Platform Symphony) to solve the state of the art problems in three different domains, which require high computing power due to high volume of data to be processed. Our general objective is two-fold: (1) testing the applicability of Platform Symphony on three diverse domains, and (2) identifying issues on which improvements to Platform Symphony are needed to better serve the needs of IBM customers. By doing so, IBM will attract more customers with different needs in the area of distributed computing. The three application problems used in this investigation are: Graph Analytics: Distributed Keyword Search in Very Large Graphs; Data Analytics: Efficient Mining of Frequent patterns from Big Data using the MapReduce Framework in Hadoop; and Multimedia Communications: Scalable Video Cloud Transcoder for Wireless Multicasts.