A Datalog Engine for GPUs
Departamento de Computacion, CINVESTAV-IPN, Av. Instituto Politecnico Nacional 2508, 07360 D.F., Mexico
22nd International Workshop on Functional and (Constraint) Logic Programming, 2013
@article{martinez2013datalog,
title={A Datalog Engine for GPUs},
author={Mart{i}nez-Angeles, Carlos Alberto and Dutra, In{^e}s and Costa, V{i}tor Santos and Buenabad-Ch{‘a}vez, Jorge},
journal={CHRISTIAN-ALBRECHTS-UNIVERSITAT ZU KIEL},
pages={239},
year={2013}
}
We present the design and evaluation of a Datalog engine for execution in Graphics Processing Units (GPUs). The engine evaluates recursive and non-recursive Datalog queries using a bottom-up approach based on typical relational operators. It includes a memory management scheme that automatically swaps data between memory in the host platform (a multicore) and memory in the GPU in order to reduce the number of memory transfers. To evaluate the performance of the engine, three Datalog queries were run on the engine and on a single CPU in the multicore host. One query runs up to 200 times faster on the (GPU) engine than on the CPU.
October 25, 2013 by hgpu
