HOUSTON, TEXAS — A research team of Rice University in Houston, Texas, the United States, will unveil this Thursday a system that would be helpful for systems programmers to deal with working pressure.
According to news release by Rice University on Monday, the PlinyCompute will be unveiled at the 2018 ACM SIGMOD/PODS conference. In a peer-reviewed conference paper, the team describes PlinyCompute as “a system purely for developing high-performance, big data codes.”
Chris Jermaine, the Rice computer science professor leading the platform’s development, said that PlinyCompute is designed to support the intense kinds of computation that have only previously been possible with supercomputers, or high-performance computers (HPC).
According to Jia Zou, a Rice research scientist and first author of the ACM SIGMOD paper, PlinyCompute is different as compared to Spark, because it was designed for high performance from the ground up.
Jia Zou, Ph.D graduate from Tsinghua University, Beijing, China, is now a research scientist in the Department of Computer Science at Rice University, where she builds systems for large scale analytics and data management.
She said, “In our benchmarking, we found PlinyCompute was at least twice as fast and in some cases 50 times faster at implementing complex object manipulation and library-style computations as compared to Spark.”
Spark is an open-source cluster-computing framework, providing an interface for programming entire clusters with implicit data parallelism and fault tolerance. Originally developed at the University of California, Berkeley’s AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since.
The annual week-long ACM SIGMOD/PODS Conference, which will conclude in Houston on Friday, is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and to exchange techniques, tools, and experiences.