IJRCS – Volume 5 Issue 2 Paper 3


Author’s Name : Krutika Paradkar | Rucha Borane | Pallavee Deshmukh | Akshay Kale | Ashwini Bhugul | Vandana Rupnar

Volume 05 Issue 02  Year 2018  ISSN No:  2349-3828  Page no: 9 – 10



Day by day there is a rapid growth in the generation of data. So, to handle such a huge amount of data there is a need of some effective techniques which avail to store, retrieve and analyze such massive data. Graphics Processing Unit (GPU) were conventionally utilized to optimize image filtering and video processing but it additionally avails to handle critical business applications where the computational power of GPU can provide significant benefits. In this paper, we propose the approach of analyzing the speed up of query execution. In GPU, the data is divided into smaller parts of data with help of threads of the GPU, SQL query is fired parallelly. The proposed approach is implemented on a SQLite database using the CUDA framework. The execution time of both CPU and GPU is analyzed.


Parallel Database; Parallel Programming; Distributed Database; Database Management


  1. Esraa Shehab, Alsayed Algergaway, Amany Sarhan “Accelerating relational database operations using both CPU and GPU co-processor
  2. Rajendra A. patta, Anuraj R. Kurup, Sandip M.Walunj “Enhancing Speed of SQL Database Operations using GPU” International Conference on Pervasive Computing:IEEE-978-1-4799-6272-3
  3. Kalle Karkkainen “Parallelism in Database Operation” Helsinki University October 2, 2012
  4. Peter Bakkum and Kevin Skadron “Accelerating SQL Database Operation on GPU with CUDA” Department of Computer Science University of Virginia,Charlottesville,VA22904, March 14,2010
  5. Glen Hordemann, Jong Kwan Lee, Andries H. Smith \Accelerated SQLite Database using GPUs”, Department of Computer Science and Engineering Texas AM University, 2010