توضیحات
ABSTRACT
Amdahl’s second law has been seen as a useful guideline for designing and evaluating balanced computer systems
for decades. This law has been mainly used for hardware systems and peak capacities. This paper utilizes Amdahl’s second law from a new angle, i.e., evaluating the influence on systems performance and balance of the application framework software, a key component of big data systems. We compare two big data application framework software systems, Apache Hadoop and DataMPI, with three representative application benchmarks and various data sizes. System monitors and hardware performance counters are used to record the resource utilization,characteristics of instructions execution, memory accesses, and I/O rates. These numbers are used to reveal the three runtime metrics of Amdahl’s second law: CPU speed (GIPS), memory capacity (GB), and I/O rate (Gbps). The experiment and evaluation results show that a DataMPI-based big data system has better performance
and is more balanced than a Hadoop-based system.
INTRODUCTION
Data explosion is becoming an irresistible trend with the development of Internet, social network, e-commerce, etc.Over the last decade, there have been emerging a lot of systems and frameworks for big data, such as MapReduce [1], Hadoop [2], Dyrad [3], Yahoo! S4 [4], Spark [5] and so on. Evaluation and comparison of these systems are becoming an important issue. Most of the previous work focuses on the performance of the big data systems, and pays less attention to system balance. In the traditional computer system area, much work has been done to help us analyze the architecture balance, such as Amdahl’s second law [6].
Year : 2014
Publisher : IEEE
By : Fan Liang , Chen Feng , Xiaoyi Lu , Zhiwei Xu
File Information : English Language / 9 Page / Size : 423 K
Download : click
سال : 2014
ناشر : IEEE
کاری از : Fan Liang , Chen Feng , Xiaoyi Lu , Zhiwei Xu
اطلاعات فایل : زبان انگلیسی / 9 صفحه / حجم : 423 K
لینک دانلود : روی همین لینک کلیک کنید
نقد و بررسیها
هنوز بررسیای ثبت نشده است.