.png){kind=icon}
.png){kind=icon}
Return
Breaking the Memory Wall in MonetDB
.png){kind=icon}
OA
AI
DOI：10.1145/1409360.1409380.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In the past decades, advances in speed of commodity CPUs have far outpaced advances in RAM latency. Main-memory access has therefore become a performance bottleneck for many computer applications; a phenomenon that is widely known as the memorywall. In this paper, we report how research around the MonetDB database system has led to a redesign of database architecture in order to take advantage of modern hardware, and in particular to avoid hitting the memory wall. This encompasses (i) a redesign of the query execution model to better exploit pipelined CPU architectures and CPU instruction caches; (ii) the use of columnar rather than row-wise data storage to better exploit CPU data caches; (iii) the design of new cache-conscious query processing algorithms; and (iv) the design and automatic calibration of memory cost models to choose and tune these cache-conscious algorithms in the query optimizer.
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
12.2
Papers:
1.2W
Citations:
3.7W
Organization
No organization information available