Name
Abstract | ||
|---|---|---|
Decision Support System (DSS) workloads are known to be one of the most time-consuming database workloads that process large data sets. Traditionally, DSS queries have been accelerated using large-scale multiprocessors. In this work we exploit the benefits of using future many-core architectures, more specifically on-chip clustered many-core architectures. To achieve this goal we propose different representative data parallel versions of the original database scan and join algorithms. We also study the impact on the performance when on-chip memory, shared among all cores, is used as a prefetching buffer. For our experiments we study the behaviour of three queries from the standard DSS benchmark TPC-H executing on the Intel Single chip Cloud Computer experimental processor (Intel SCC). Our results show that parallelism can be well exploited by such architectures and how important it is to have a balance between computation and data intensity. Moreover, from our experimental results we show that performance improvement of 5x and 10x for the corresponding query implementation without data prefetching. Finally we show how we could efficiently use the system in order to achieve high power-performance efficiency when using the proposed prefetching buffer. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/PDP.2013.14 | PDP |
Keywords | Field | DocType |
data intensity,prefetching,multiprocessor system,database workloads,shared memory,prefetching buffer,different representative data,database workload,cloud computer experimental processor,parallel architectures,buffer storage,large data set,proposed prefetching buffer,standard dss benchmark tpc-h,tpc-h,on-chip clustered manycore architecture,database queries,dss,intel scc,shared memory systems,decision support systems,query implementation,queries optimization,decision support system,database query,dss query,coprocessors,intel single chip,future many-core systems,intel single chip cloud computer,future manycore architecture,parallel architecture,query processing,on-chip memory | System on a chip,Computer science,Decision support system,Parallel computing,Exploit,Coprocessor,Benchmark (computing),Database,Performance improvement,Distributed computing,Scalability,Single-chip Cloud Computer | Conference |
ISSN | ISBN | Citations |
1066-6192 E-ISBN : 978-0-7695-4939-2 | 978-0-7695-4939-2 | 2 |
PageRank | References | Authors |
0.37 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Panayiotis Petrides | 1 | 12 | 3.11 |
| Andreas Diavastos | 2 | 9 | 4.48 |
| Constantinos Christofi | 3 | 2 | 0.37 |
| Pedro Trancoso | 4 | 377 | 43.79 |