申请试用
HOT
登录
注册
 
Rethinking SIMD Vectorization for In-Memory Databases

Rethinking SIMD Vectorization for In-Memory Databases

陈傲天
/
发布于
/
2015
人观看
Our evaluation on the MIC-based Xeon Phi co-processor as well as the latest mainstream CPUs shows that our vectorization designs are up to an order of magnitude faster than the state-of-the-art scalar and vector approaches. Also, we highlight the impact of efficient vectorization on the algorithmic design of in-memory database operators, as well as the architectural design and power efficiency of hardware, by making simple cores comparably fast to complex cores. This work is applicable to CPUs and co-processors with advanced SIMD capabilities, using either many simple cores or fewer complex cores.
15 点赞
4 收藏
1下载
确认
3秒后跳转登录页面
去登陆