We introduce SparkCL, an open source unified programming framework based on Java, OpenCL and the Apache Spark framework. The motivation behind this work is to bring unconventional compute cores such as FPGAs/GPUs/APUs/DSPs and future core types into mainstream programming use. The framework allows equal treatment of different computing devices under the Spark framework and introduces the abilit...

Apache Spark is a popular framework for data analytics with attractive features such as fault tolerance and interoperability with the Hadoop ecosystem. Unfortunately, many analytics operations in Spark are an order of magnitude or more slower compared to native implementations written with high performance computing tools such as MPI. There is a need to bridge the performance gap while retainin...

Spark is gaining wide industry adoption due to its superior performance, simple interfaces, and a rich library for analysis and calculation. Like many projects in the big data ecosystem, Spark runs on the Java Virtual Machine (JVM). Because Spark can store large amounts of data in memory, it has a major reliance on Java’s memory management and garbage collection (GC). New initiatives like Proje...

MapReduce and Spark are two very popular open source cluster computing frameworks for large scale data analytics. These frameworks hide the complexity of task parallelism and fault-tolerance, by exposing a simple programming API to users. In this paper, we evaluate the major architectural components in MapReduce and Spark frameworks including: shuffle, execution model, and caching, by using a s...

The article describes a nonlinear theory of how the presence third elements affects results analyzing elemental composition substances by means atomic emission spectroscopy. is based on assumption that there an arbitrary relationship between intensity analytical line analyte and concentration impurities alloying elements. has been tested simulation problem using commercially available equipment...

Some modern alloys, such as high-entropy alloys (HEAs), are emerging with greater acceleration due to their wide range of properties and applications. HEAs can be prepared from many metallurgical operations, but mechanical alloying is considered one the most simple, economical, popular, suitable methods its increased solid solubility, nano-crystalline structure, homogeneity, room-temperature pr...