Datalog for GPUs

Carlos Alberto Martinez Angeles
Centro de Investigacion y de Estudios Avanzados del Instituto Politecnico Nacional
Instituto Politecnico Nacional, 2013

   title={Datalog for GPUs},

   author={Carlos Alberto Martinez Angeles},



Download Download (PDF)   View View   Source Source   
Datalog is a language based on first order logic that was investigated as a data model for relational databases in the 1980s. It has recently been used in various new application areas, prompting proposals to run Datalog programs on new platforms such as Graphics Processing Units (GPUs) and MapReduce. Back then and nowadays, interest in Datalog has stemmed from its ability to compute the transitive closure of relations through recursive queries which, in efect, turns relational databases into deductive databases, or knowledge bases. This thesis presents the design, implementation and evaluation of a Datalog engine for GPUs. It is the rst fully functional Datalog engine for GPUs to the best of our knowledge. It consists of: i) a compiler that translates Datalog programs into relational algebra operations (select, various types of joins and project); ii) a scheduler that plans and launches such operations into the GPU from the host platform; iii) the GPU parallel algorithms of such operations; and iv) a memory management scheme that tends to reduce the number of memory transfers between the host and the GPU. It also includes various optimisations that capitalise on the characteristics of the Datalog language and the GPU architecture. Our Datalog engine was developed in C with the Nvidia CUDA software platform. The evaluation of our engine using several queries shows a dramatic performance improvement when compared against the well known Prolog engines XSB and YAP, and the Datalog engine from Mitre Corporation. For two of the queries, a performance increase of up to 200 times was achieved.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

You must be logged in to post a comment.

* * *

* * *

* * *

Free GPU computing nodes at

Registered users can now run their OpenCL application at We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 11.4
  • SDK: AMD APP SDK 2.8
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 5.0.35, AMD APP SDK 2.8

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to will be treated according to our Privacy Policy

HGPU group © 2010-2014

All rights belong to the respective authors

Contact us: