Quickstep

Quickstep is a next-generation relational data processing kernel developed in the Computer Sciences Department at the University of Wisconsin. Quickstep aims to deliver efficient and sustainable data processing performance on current and future hardware by using a hardware-software co-design philosophy.

For the hardware available today, this means effectively exploiting large main memories, fast on-die CPU caches, highly parallel multi-core CPUs, and NVRAM storage technologies.

For the hardware available in the future, we aim to co-design hardware and software primitives that will allow data processing kernels to work on increasing amounts of data economically -- both from the raw performance perspective, and from the perspective of the energy consumed by data processing kernels.

Quickstep is an open-source project! You can find the code here.

The contributor of this project are:

• Harshad Deshmukh
• Jianqiao Zhu
• Navneet Potti
• Zuyu Zhang
• Marc Spehlmann
• Hakan Memisoglu
• Saket Saurabh
• Craig Chasseur
• Qiang Zeng
• Shoban Chandrabose
• James Paton
• Udip Pant
• Adalbert G. Soosai Raj
• Jignesh M. Patel

Publications and Software

• Quickstep: A Data Platform Based on the Scaling-Up Approach, The Quickstep Team. VLDB 2018.

• The case against specialized graph analytics engines, J. Fan, G. Soosai Raj, and J. M. Patel. CIDR 2015. Slides.

• QuickFOIL: Scalable Inductive Logic Programming, Q. Zeng, J. M. Patel, and D. Page. VLDB 2015.

• Profiling R on a Contemporary Processor, S. Sridharan and J. M. Patel, VLDB 2015 (to appear). Extended paper.
  Download code and scripts.

• WideTable: An Accelerator for Analytical Data Processing, Y. Li and J. M. Patel, VLDB 2014. blog.

• Design and Evaluation of Storage Organizations For Read-Optimized Main-Memory Databases, C. Chasseur and J. M. Patel, VLDB 2014.
  Download v0.1 of the Quickstep Storage Manager, released under license; start with the README file.

• BitWeaving: Fast Scans for Main Memory Data Processing, Y. Li and J. M. Patel, SIGMOD 2013.

• Enabling JSON Document Stores in Relational Systems, C. Chasseur, Y. Li, and J. M. Patel, WebDB 2013.
  Download the Argo mapping layer. Download the NoBench benchmark.

Support

Quickstep is supported in part by the National Science Foundation under grants IIS-0963993 and IIS-1250886.