Abstract
Big data is a hot topic that is regularly discussed in the computer science field for the past year. Big data provides numerous benefits for the development of technologies, such as business intelligence and deep learning. Processing big data requires specialized tools and environment, ranging from a commodity-clustered workstation to high performance computing server, especially in big data clustering where unsupervised learning takes place. In this paper, we conduct time analysis of commodity-clustered workstation equipped with Spark as a baseline for multi-CPU big data clustering and TensorFlow installed in a high-performance computing workstation as a baseline for multi-GPU big data clustering. Based on the analysis, it shows that TensorFlow performs have around 5 to 12 times faster computation time than Spark.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
