The Project SINDPAD
Parallelization becomes more and
more important, even for the architecture of single machines. Recent
advances in processor technologies achieve only small performance
improvements for single cores. Increasing the compute power of modern
architectures mandates to increase the number of compute cores on a
single central processing unit (CPU). Graphics Processing Units(GPUs)
have a long history of scale-out through parallel processing on many
compute cores. Graphics adapters nowadays offer a highly parallel
execution environment that within the context of GPGPU (General
purpose Processing in Graphics Processing Units) is frequently used in
scientific computing. The challenge of GPGPU programming is to design
applications for the SIMD architecture (Single Instruction, Multiple
Data) of graphics adapters that allow only for a limited range of
operators and very limited synchronization mechanisms.
In the course of the SINDPAD project, we will develop an indexing and search technology for structured data sets. We will leverage graphics adapters to support query execution. SindPad aims at achieving unprecedented performance compared to conventional systems of equal cost. We consider taking advantage of application characteristics to accelerate data processing. Especially for Business Intelligence (BI) applications, the schema enables the system to store specific data on graphics adapters. This can lead to further speed ups.
Researchers of the Database Systems and Information Management (DIMA) group at the TU Berlin will play a significant role in the conceptual planning and implementation of algorithms for hybrid GPU/CPU processing. We will analyze query processing algorithms and devise metrics to compare the performance of GPU-operators and CPU-operators .The SINDPAD project is funded by the German Federal Ministry of Economics and Technology and is carried out in cooperation with empulse GmbH.