The passage discusses the use of technology in vehicle fuel systems, specifically injection system that is replacing conventional systems. One crucial component Engine Control Unit (ECU), which controls distribution current to all engine components. While standard ECUs used on motorcycles today have limitations, racing provide more quality and can improve performance. study aims evaluate engine...

With tremendous growing interests in Big Data systems, analyzing and facilitating their performance improvement become increasingly important. Although there have much research efforts for improving Big Data systems performance, efficiently analysing and diagnosing performance bottlenecks over these massively distributed systems remain a major challenge. In this paper, we propose a spatio-tempo...

Cluster computing systems today impose a trade-off between generality, performance and productivity. Hadoop and Dryad force programmers to write low level programs that are tedious to compose but easy to optimize. Systems like Dryad/LINQ and Spark allow concise modeling of user programs but do not apply relational optimizations. Pig and Hive restrict the language to achieve relational optimizat...

With the ever-increasing need to analyze large amounts of data to get useful insights, it is essential to develop complex parallel machine learning algorithms that can scale with data and number of parallel processes. These algorithms need to run on large data sets as well as they need to be executed with minimal time in order to extract useful information in a time constrained environment. MPI...

We benchmarked Apache Spark with a popular parallel machine learning training application, Distributed Stochastic Gradient Descent for Matrix Factorization [5] and compared the Spark implementation with alternative approaches for communicating model parameters, such as scheduled pipelining using POSIX socket or MPI, and distributed shared memory (e.g. parameter server [13]). We found that Spark...

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...

The Simulation Problem Analysis and Research Kernel (SPARK) uses graph-theoretic techniques to match equations to variables and build computational graphs, yielding solution sequences indicated by needed data flow. Additionally, the problem graph is decomposed into strongly connected components, thus reducing the size of simultaneous equation sets, and small cut sets are determined, thereby red...

.........................................................................................................................3 INTRODUCTION ................................................................................................................5 DIESEL ENGINE TECHNOLOGY AND EMISSION REGULATIONS .............................7 PHYSICAL AND CHEMICAL NATURE OF DIESEL AEROSOL ......................

During the 2015-2016 academic year, I conducted research about Spark, BlinkDB and various sampling techniques. This research helped the team have a better understanding of the capabilities and properties of Spark, BlinkDB system and different sampling technologies. Additionally, I benchmarked and implemented various Machine learning and sampling methods on the top of both Spark and BlinkDB. The...