This survey paper reviews how the Graphical Processing Unit (GPU) can be leveraged by accelerating queries for the Relational Database Management System. Queries can be accelerated in many ways like optimizing primitives, using an opcode execution model, using an in memory database, kernel fusion, batching and data placement. Data trans-fer remains a significant bottleneck and thus the mitigation methods such as database compression, differential update and unified address space are reviewed
© 2020 Association for Computing Machinery. There has been significant amount of excitement and rece...
We present GPUQP, a relational query engine that employs both CPUs and GPUs (Graphics Processing Uni...
textabstractExisting work on accelerating analytic DB query processing with (discrete) GPUs fails t...
Abstract. The vast amount of processing power and memory band-width provided by modern graphics card...
This paper introduces the development of a new GPU-based database to accelerate data retrieval. The ...
This thesis first maps the relational computation onto Graphics Processing Units (GPU)s by designing...
Graphics processors (GPUs) have recently emerged as a powerful co-processor for general-purpose comp...
The variety of memory devices in modern computer systems holds opportunities as well as challenges f...
Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)...
Current database management systems use Graphic Processing Units (GPUs) as dedicated accelerators to...
GPU acceleration is a promising approach to speed up query processing of database systems by using l...
Modern enterprise applications represent an emergent ap-plication arena that requires the processing...
Graphics processors (GPUs) have recently emerged as powerful coprocessors for general purpose comput...
AbstractThis study is devoted to exploring possible applications of GPU technology for acceleration ...
The variety of memory devices in modern com- puter systems holds opportunities as well as challenges...
© 2020 Association for Computing Machinery. There has been significant amount of excitement and rece...
We present GPUQP, a relational query engine that employs both CPUs and GPUs (Graphics Processing Uni...
textabstractExisting work on accelerating analytic DB query processing with (discrete) GPUs fails t...
Abstract. The vast amount of processing power and memory band-width provided by modern graphics card...
This paper introduces the development of a new GPU-based database to accelerate data retrieval. The ...
This thesis first maps the relational computation onto Graphics Processing Units (GPU)s by designing...
Graphics processors (GPUs) have recently emerged as a powerful co-processor for general-purpose comp...
The variety of memory devices in modern computer systems holds opportunities as well as challenges f...
Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)...
Current database management systems use Graphic Processing Units (GPUs) as dedicated accelerators to...
GPU acceleration is a promising approach to speed up query processing of database systems by using l...
Modern enterprise applications represent an emergent ap-plication arena that requires the processing...
Graphics processors (GPUs) have recently emerged as powerful coprocessors for general purpose comput...
AbstractThis study is devoted to exploring possible applications of GPU technology for acceleration ...
The variety of memory devices in modern com- puter systems holds opportunities as well as challenges...
© 2020 Association for Computing Machinery. There has been significant amount of excitement and rece...
We present GPUQP, a relational query engine that employs both CPUs and GPUs (Graphics Processing Uni...
textabstractExisting work on accelerating analytic DB query processing with (discrete) GPUs fails t...