A system purely for developing high-performance, big data codes

IMAGE: This is the Rice University's PlinyCompute team includes (from left) Shangyu Luo, Sourav Sikdar, Jia Zou, Tania Lorido, Binhang Yuan, Jessica Yu, Chris Jermaine, Carlos Monroy, Dimitrije Jankov and Matt... view more HOUSTON -- (June 11, 2018) -- Computer scientists from Rice University's DARPA-funded Pliny Project believe they have the answer for every stressed-out systems programmer who has struggled to implement complex objects and workflows on'big data' platforms like Spark and thought: "Isn't there a better way?" Rice's PlinyCompute will be unveiled here Thursday at the 2018 ACM SIGMOD conference. In a peer-reviewed conference paper, the team describes PlinyCompute as "a system purely for developing high-performance, big data codes." Like Spark, PlinyCompute aims for ease of use and broad versatility, said Chris Jermaine, the Rice computer science professor leading the platform's development. Unlike Spark, PlinyCompute is designed to support the intense kinds of computation that have only previously been possible with supercomputers, or high-performance computers (HPC). "With machine learning, and especially deep learning, people have seen what complex analytics algorithms can do when they're applied to big data," Jermaine said.