Titlebook: Big Data Benchmarks, Performance Optimization, and Emerging Hardware; 4th and 5th Workshop Jianfeng Zhan,Rui Han,Chuliang Weng Conference p

兽皮

FOIL

Folklore

curettage

Performance Benefits of DataMPI: A Case Study with BigDataBench7 % and 50 % speedups compared with those of Hadoop and Spark, respectively. Most of the benefits come from the high-efficiency communication mechanisms in DataMPI. We also notice that the resource (CPU, memory, disk and network I/O) utilizations of DataMPI are also more efficient than those of the other two frameworks.

Carcinoma

发酵

Efficient HTTP Based I/O on Very Large Datasets for High Performance Computing with the Libdavix Libes of HTTP. Then, we describe in detail how we solved these issues. Our solutions have been implemented in a toolkit called davix, available through several recent Linux distributions..Finally, we describe the results of our benchmarks where we compare the performance of davix against a HPC specific protocol for a data analysis use case.

acrimony

粗鄙的人

https://doi.org/10.1007/978-3-031-41985-0the tool kits are suited for a specific environment. In this paper we propose DSIMBench, a benchmark containing two classic microarray analysis functions with eight different parallel R workflows, and evaluate the benchmark in the IC Cloud testbed platform.

LOPE

颠簸下上

Computational Morphology Tasks,ks to evaluate and compare big data systems has become an active topic for both research and industry communities. To date, most of the state-of-the-art big data benchmarks are designed for specific types of systems. Based on our experience, however, we argue that considering the complexity, diversi