HPAT: High Performance Analytics with Scripting Ease-of-Use



Big data analytics requires high programmer productivity and high performance simultaneously on large-scale clusters. However, current big data analytics frameworks (e.g. Apache Spark) have prohibitive runtime overheads since they are library-based. We introduce a novel auto-parallelizing compiler approach that exploits the characteristics of the data analytics domain such as the map/reduce parallel pattern and is robust, unlike previous auto-parallelization methods...